Deep learning (English Wikipedia)

Socher, Richard; Bauer, John; Manning, Christopher; Ng, Andrew (2013). "Parsing With Compositional Vector Grammars" (PDF). Proceedings of the ACL 2013 Conference. Archived (PDF) from the original on 2014-11-27. Retrieved 2014-09-03.

acm.org

dl.acm.org

Robinson, T. (1992). "A real-time recurrent error propagation network word recognition system". ICASSP. Icassp'92: 617–620. ISBN 9780780305328. Archived from the original on 2021-05-09. Retrieved 2017-06-12.
You, Yang; Buluç, Aydın; Demmel, James (November 2017). "Scaling deep learning on GPU and knights landing clusters". Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17. SC '17, ACM. pp. 1–12. doi:10.1145/3126908.3126912. ISBN 9781450351140. S2CID 8869270. Archived from the original on 29 July 2020. Retrieved 5 March 2018.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (1 January 2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM. pp. 533–540. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210. Archived from the original on 9 May 2021. Retrieved 23 November 2015.

awards.acm.org

"2018 ACM A.M. Turing Award Laureates". awards.acm.org. Retrieved 2024-08-07.

airesearch.com

Research, AI (23 October 2015). "Deep Neural Networks for Acoustic Modeling in Speech Recognition". airesearch.com. Archived from the original on 1 February 2016. Retrieved 23 October 2015.

apa.org

doi.apa.org

Rosenblatt, F. (1958). "The perceptron: A probabilistic model for information storage and organization in the brain". Psychological Review. 65 (6): 386–408. doi:10.1037/h0042519. ISSN 1939-1471. PMID 13602029.

archive.org

Smolensky, Paul (1986). "Chapter 6: Information Processing in Dynamical Systems: Foundations of Harmony Theory" (PDF). In Rumelhart, David E.; McLelland, James L. (eds.). Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Volume 1: Foundations. MIT Press. pp. 194–281. ISBN 0-262-68053-X.

arxiv.org

Ciresan, D.; Meier, U.; Schmidhuber, J. (2012). "Multi-column deep neural networks for image classification". 2012 IEEE Conference on Computer Vision and Pattern Recognition. pp. 3642–3649. arXiv:1202.2745. doi:10.1109/cvpr.2012.6248110. ISBN 978-1-4673-1228-8. S2CID 2161592.
Bengio, Y.; Courville, A.; Vincent, P. (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. doi:10.1109/tpami.2013.50. PMID 23787338. S2CID 393948.
Schmidhuber, J. (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Sonoda, Sho; Murata, Noboru (2017). "Neural network with unbounded activation functions is universal approximator". Applied and Computational Harmonic Analysis. 43 (2): 233–268. arXiv:1505.03654. doi:10.1016/j.acha.2015.12.005. S2CID 12149203.
Schmidhuber, Jürgen (2022). "Annotated History of Modern AI and Deep Learning". arXiv:2212.11279 [cs.NE].
Ramachandran, Prajit; Barret, Zoph; Quoc, V. Le (October 16, 2017). "Searching for Activation Functions". arXiv:1710.05941 [cs.NE].
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks. 127: 58–66. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008. PMID 32334341. S2CID 216056336.
Sze, Vivienne; Chen, Yu-Hsin; Yang, Tien-Ju; Emer, Joel (2017). "Efficient Processing of Deep Neural Networks: A Tutorial and Survey". arXiv:1703.09039 [cs.CV].
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (21 September 2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation. 22 (12): 3207–3220. arXiv:1003.0358. doi:10.1162/neco_a_00052. ISSN 0899-7667. PMID 20858131. S2CID 1918673.
Ng, Andrew; Dean, Jeff (2012). "Building High-level Features Using Large Scale Unsupervised Learning". arXiv:1112.6209 [cs.LG].
Simonyan, Karen; Andrew, Zisserman (2014). "Very Deep Convolution Networks for Large Scale Image Recognition". arXiv:1409.1556 [cs.CV].
Szegedy, Christian (2015). "Going deeper with convolutions" (PDF). Cvpr2015. arXiv:1409.4842.
Vinyals, Oriol; Toshev, Alexander; Bengio, Samy; Erhan, Dumitru (2014). "Show and Tell: A Neural Image Caption Generator". arXiv:1411.4555 [cs.CV]..
Fang, Hao; Gupta, Saurabh; Iandola, Forrest; Srivastava, Rupesh; Deng, Li; Dollár, Piotr; Gao, Jianfeng; He, Xiaodong; Mitchell, Margaret; Platt, John C; Lawrence Zitnick, C; Zweig, Geoffrey (2014). "From Captions to Visual Concepts and Back". arXiv:1411.4952 [cs.CV]..
Kiros, Ryan; Salakhutdinov, Ruslan; Zemel, Richard S (2014). "Unifying Visual-Semantic Embeddings with Multimodal Neural Language Models". arXiv:1411.2539 [cs.LG]..
Simonyan, Karen; Zisserman, Andrew (2015-04-10), Very Deep Convolutional Networks for Large-Scale Image Recognition, arXiv:1409.1556
He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian (2016). "Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification". arXiv:1502.01852 [cs.CV].
He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian (10 Dec 2015). Deep Residual Learning for Image Recognition. arXiv:1512.03385.
He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian (2016). Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA: IEEE. pp. 770–778. arXiv:1512.03385. doi:10.1109/CVPR.2016.90. ISBN 978-1-4673-8851-1.
Gatys, Leon A.; Ecker, Alexander S.; Bethge, Matthias (26 August 2015). "A Neural Algorithm of Artistic Style". arXiv:1508.06576 [cs.CV].
Karras, T.; Aila, T.; Laine, S.; Lehtinen, J. (26 February 2018). "Progressive Growing of GANs for Improved Quality, Stability, and Variation". arXiv:1710.10196 [cs.NE].
Sohl-Dickstein, Jascha; Weiss, Eric; Maheswaranathan, Niru; Ganguli, Surya (2015-06-01). "Deep Unsupervised Learning using Nonequilibrium Thermodynamics" (PDF). Proceedings of the 32nd International Conference on Machine Learning. 37. PMLR: 2256–2265. arXiv:1503.03585.
Singh, Premjeet; Saha, Goutam; Sahidullah, Md (2021). "Non-linear frequency warping using constant-Q transformation for speech emotion recognition". 2021 International Conference on Computer Communication and Informatics (ICCCI). pp. 1–4. arXiv:2102.04029. doi:10.1109/ICCCI50826.2021.9402569. ISBN 978-1-7281-5875-4. S2CID 231846518.
Li, Xiangang; Wu, Xihong (2014). "Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition". arXiv:1410.4281 [cs.CL].
Kumar, Nishant; Raubal, Martin (2021). "Applications of deep learning in congestion detection, prediction and alleviation: A survey". Transportation Research Part C: Emerging Technologies. 133: 103432. arXiv:2102.09759. Bibcode:2021TRPC..13303432K. doi:10.1016/j.trc.2021.103432. hdl:10230/42143. S2CID 240420107.
Sutskever, L.; Vinyals, O.; Le, Q. (2014). "Sequence to Sequence Learning with Neural Networks" (PDF). Proc. NIPS. arXiv:1409.3215. Bibcode:2014arXiv1409.3215S. Archived (PDF) from the original on 2021-05-09. Retrieved 2017-06-13.
Jozefowicz, Rafal; Vinyals, Oriol; Schuster, Mike; Shazeer, Noam; Wu, Yonghui (2016). "Exploring the Limits of Language Modeling". arXiv:1602.02410 [cs.CL].
Gillick, Dan; Brunk, Cliff; Vinyals, Oriol; Subramanya, Amarnag (2015). "Multilingual Language Processing from Bytes". arXiv:1512.00103 [cs.CL].
Bengio, Yoshua; Boulanger-Lewandowski, Nicolas; Pascanu, Razvan (2013). "Advances in optimizing recurrent networks". 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 8624–8628. arXiv:1212.0901. CiteSeerX 10.1.1.752.9151. doi:10.1109/icassp.2013.6639349. ISBN 978-1-4799-0356-6. S2CID 12485056.
Viebke, André; Memeti, Suejb; Pllana, Sabri; Abraham, Ajith (2019). "CHAOS: a parallelization scheme for training convolutional neural networks on Intel Xeon Phi". The Journal of Supercomputing. 75: 197–227. arXiv:1702.07908. Bibcode:2017arXiv170207908V. doi:10.1007/s11227-017-1994-x. S2CID 14135321.
P, JouppiNorman; YoungCliff; PatilNishant; PattersonDavid; AgrawalGaurav; BajwaRaminder; BatesSarah; BhatiaSuresh; BodenNan; BorchersAl; BoyleRick (2017-06-24). "In-Datacenter Performance Analysis of a Tensor Processing Unit". ACM SIGARCH Computer Architecture News. 45 (2): 1–12. arXiv:1704.04760. doi:10.1145/3140659.3080246.
Feldmann, J.; Youngblood, N.; Karpov, M.; et al. (2021). "Parallel convolutional processing using an integrated photonic tensor". Nature. 589 (2): 52–58. arXiv:2002.00281. doi:10.1038/s41586-020-03070-1. PMID 33408373. S2CID 211010976.
Hannun, Awni; Case, Carl; Casper, Jared; Catanzaro, Bryan; Diamos, Greg; Elsen, Erich; Prenger, Ryan; Satheesh, Sanjeev; Sengupta, Shubho; Coates, Adam; Ng, Andrew Y (2014). "Deep Speech: Scaling up end-to-end speech recognition". arXiv:1412.5567 [cs.CL].
Chaochao Lu; Xiaoou Tang (2014). "Surpassing Human Level Face Recognition". arXiv:1404.3840 [cs.CV].
Goldberg, Yoav; Levy, Omar (2014). "word2vec Explained: Deriving Mikolov et al.'s Negative-Sampling Word-Embedding Method". arXiv:1402.3722 [cs.CL].
Wu, Yonghui; Schuster, Mike; Chen, Zhifeng; Le, Quoc V; Norouzi, Mohammad; Macherey, Wolfgang; Krikun, Maxim; Cao, Yuan; Gao, Qin; Macherey, Klaus; Klingner, Jeff; Shah, Apurva; Johnson, Melvin; Liu, Xiaobing; Kaiser, Łukasz; Gouws, Stephan; Kato, Yoshikiyo; Kudo, Taku; Kazawa, Hideto; Stevens, Keith; Kurian, George; Patil, Nishant; Wang, Wei; Young, Cliff; Smith, Jason; Riesa, Jason; Rudnick, Alex; Vinyals, Oriol; Corrado, Greg; et al. (2016). "Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation". arXiv:1609.08144 [cs.CL].
Wallach, Izhar; Dzamba, Michael; Heifets, Abraham (9 October 2015). "AtomNet: A Deep Convolutional Neural Network for Bioactivity Prediction in Structure-based Drug Discovery". arXiv:1510.02855 [cs.LG].
Gilmer, Justin; Schoenholz, Samuel S.; Riley, Patrick F.; Vinyals, Oriol; Dahl, George E. (2017-06-12). "Neural Message Passing for Quantum Chemistry". arXiv:1704.01212 [cs.LG].
Tkachenko, Yegor (8 April 2015). "Autonomous CRM Control via CLV Approximation with Deep Reinforcement Learning in Discrete and Continuous Action Space". arXiv:1504.01840 [cs.LG].
Shalev, Y.; Painsky, A.; Ben-Gal, I. (2022). "Neural Joint Entropy Estimation" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (4): 5488–5500. arXiv:2012.11197. doi:10.1109/TNNLS.2022.3204919. PMID 36155469. S2CID 229339809.
Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (December 2017). "A survey on deep learning in medical image analysis". Medical Image Analysis. 42: 60–88. arXiv:1702.05747. Bibcode:2017arXiv170205747L. doi:10.1016/j.media.2017.07.005. PMID 28778026. S2CID 2088679.
Han, J.; Jentzen, A.; E, W. (2018). "Solving high-dimensional partial differential equations using deep learning". Proceedings of the National Academy of Sciences. 115 (34): 8505–8510. arXiv:1707.02568. Bibcode:2018PNAS..115.8505H. doi:10.1073/pnas.1718942115. PMC 6112690. PMID 30082389.
Oktem, Figen S.; Kar, Oğuzhan Fatih; Bezek, Can Deniz; Kamalabadi, Farzad (2021). "High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction". IEEE Transactions on Computational Imaging. 7: 489–504. arXiv:2008.11625. doi:10.1109/TCI.2021.3075349. ISSN 2333-9403. S2CID 235340737.
Bernhardt, Melanie; Vishnevskiy, Valery; Rau, Richard; Goksel, Orcun (December 2020). "Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67 (12): 2584–2594. arXiv:2006.14395. doi:10.1109/TUFFC.2020.3010186. ISSN 1525-8955. PMID 32746211. S2CID 220055785.
Lam, Remi; Sanchez-Gonzalez, Alvaro; Willson, Matthew; Wirnsberger, Peter; Fortunato, Meire; Alet, Ferran; Ravuri, Suman; Ewalds, Timo; Eaton-Rosen, Zach; Hu, Weihua; Merose, Alexander; Hoyer, Stephan; Holland, George; Vinyals, Oriol; Stott, Jacklynn (2023-12-22). "Learning skillful medium-range global weather forecasting". Science. 382 (6677): 1416–1421. arXiv:2212.12794. Bibcode:2023Sci...382.1416L. doi:10.1126/science.adi2336. ISSN 0036-8075. PMID 37962497.
Güçlü, Umut; van Gerven, Marcel A. J. (8 July 2015). "Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream". Journal of Neuroscience. 35 (27): 10005–10014. arXiv:1411.6422. doi:10.1523/jneurosci.5023-14.2015. PMC 6605414. PMID 26157000.
Nguyen, Anh; Yosinski, Jason; Clune, Jeff (2014). "Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images". arXiv:1412.1897 [cs.CV].
Szegedy, Christian; Zaremba, Wojciech; Sutskever, Ilya; Bruna, Joan; Erhan, Dumitru; Goodfellow, Ian; Fergus, Rob (2013). "Intriguing properties of neural networks". arXiv:1312.6199 [cs.CV].

blog.google

Turovsky, Barak (15 November 2016). "Found in translation: More accurate, fluent sentences in Google Translate". The Keyword Google Blog. Archived from the original on 7 April 2017. Retrieved 23 March 2017.

books.google.com

Shigeki, Sugiyama (12 April 2019). Human Behavior and Another Kind in Consciousness: Emerging Research and Opportunities: Emerging Research and Opportunities. IGI Global. ISBN 978-1-5225-8218-2.
Haykin, Simon S. (1999). Neural Networks: A Comprehensive Foundation. Prentice Hall. ISBN 978-0-13-273350-2.
Hassoun, Mohamad H. (1995). Fundamentals of Artificial Neural Networks. MIT Press. p. 48. ISBN 978-0-262-08239-6.
Murphy, Kevin P. (24 August 2012). Machine Learning: A Probabilistic Perspective. MIT Press. ISBN 978-0-262-01802-9.
Ivakhnenko, A. G.; Lapa, V. G. (1967). Cybernetics and Forecasting Techniques. American Elsevier Publishing Co. ISBN 978-0-444-00020-0.
Leibniz, Gottfried Wilhelm Freiherr von (1920). The Early Mathematical Manuscripts of Leibniz: Translated from the Latin Texts Published by Carl Immanuel Gerhardt with Critical and Historical Notes (Leibniz published the chain rule in a 1676 memoir). Open court publishing Company. ISBN 9780598818461.
Hochreiter, S.; et al. (15 January 2001). "Gradient flow in recurrent nets: the difficulty of learning long-term dependencies". In Kolen, John F.; Kremer, Stefan C. (eds.). A Field Guide to Dynamical Recurrent Networks. John Wiley & Sons. ISBN 978-0-7803-5369-5.
Yu, D.; Deng, L. (2014). Automatic Speech Recognition: A Deep Learning Approach (Publisher: Springer). Springer. ISBN 978-1-4471-5779-3.
Elman, Jeffrey L. (1998). Rethinking Innateness: A Connectionist Perspective on Development. MIT Press. ISBN 978-0-262-55030-7.

cam.ac.uk

www-control.eng.cam.ac.uk

Ting Qin, et al. "Continuous CMAC-QRLS and its systolic array". Archived 2018-11-18 at the Wayback Machine. Neural Processing Letters 22.1 (2005): 1-16.

cell.com

Hinton, Geoffrey E. (1 October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. ISSN 1364-6613. PMID 17921042. S2CID 15066318. Archived from the original on 11 October 2013. Retrieved 12 June 2017.

cern.ch

indico.cern.ch

Yann LeCun (2016). Slides on Deep Learning Online Archived 2016-04-23 at the Wayback Machine

cmu.edu

deeplearning.cs.cmu.edu

Cybenko (1989). "Approximations by superpositions of sigmoidal functions" (PDF). Mathematics of Control, Signals, and Systems. 2 (4): 303–314. Bibcode:1989MCSS....2..303C. doi:10.1007/bf02551274. S2CID 3958369. Archived from the original (PDF) on 10 October 2015.

cnbc.com

Shead, Sam (2020-11-30). "DeepMind solves 50-year-old 'grand challenge' with protein folding A.I." CNBC. Retrieved 2024-05-10.

coursera.org

"Data Augmentation - deeplearning.ai | Coursera". Coursera. Archived from the original on 1 December 2017. Retrieved 30 November 2017.

dailydot.com

"How hackers can force AI to make dumb mistakes". The Daily Dot. 18 June 2018. Archived from the original on 11 October 2019. Retrieved 11 October 2019.

datanami.com

Woodie, Alex (2021-11-01). "Cerebras Hits the Accelerator for Deep Learning Workloads". Datanami. Retrieved 2022-08-03.

datascienceassn.org

"Multi-task Neural Networks for QSAR Predictions | Data Science Association". www.datascienceassn.org. Archived from the original on 30 April 2017. Retrieved 14 June 2017.

dml.cz

Waibel, A.; Hanazawa, T.; Hinton, G.; Shikano, K.; Lang, K. J. (March 1989). "Phoneme recognition using time-delay neural networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 37 (3): 328–339. doi:10.1109/29.21701. hdl:10338.dmlcz/135496. ISSN 0096-3518. S2CID 9563026. Archived (PDF) from the original on 2021-04-27. Retrieved 2019-09-24.

doi.org

Schulz, Hannes; Behnke, Sven (1 November 2012). "Deep Learning". KI - Künstliche Intelligenz. 26 (4): 357–363. doi:10.1007/s13218-012-0198-z. ISSN 1610-1987. S2CID 220523562.
LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep Learning" (PDF). Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442. S2CID 3074096.
Ciresan, D.; Meier, U.; Schmidhuber, J. (2012). "Multi-column deep neural networks for image classification". 2012 IEEE Conference on Computer Vision and Pattern Recognition. pp. 3642–3649. arXiv:1202.2745. doi:10.1109/cvpr.2012.6248110. ISBN 978-1-4673-1228-8. S2CID 2161592.
Bengio, Yoshua (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. S2CID 207178999. Archived from the original (PDF) on 4 March 2016. Retrieved 3 September 2015.
Bengio, Y.; Courville, A.; Vincent, P. (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. doi:10.1109/tpami.2013.50. PMID 23787338. S2CID 393948.
Schmidhuber, J. (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Hinton, G.E. (2009). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.
Aizenberg, I.N.; Aizenberg, N.N.; Vandewalle, J. (2000). Multi-Valued and Universal Binary Neurons. Science & Business Media. doi:10.1007/978-1-4757-3115-6. ISBN 978-0-7923-7824-2. Retrieved 27 December 2023.
Fradkov, Alexander L. (2020-01-01). "Early History of Machine Learning". IFAC-PapersOnLine. 21st IFAC World Congress. 53 (2): 1385–1390. doi:10.1016/j.ifacol.2020.12.1888. ISSN 2405-8963. S2CID 235081987.
Cybenko (1989). "Approximations by superpositions of sigmoidal functions" (PDF). Mathematics of Control, Signals, and Systems. 2 (4): 303–314. Bibcode:1989MCSS....2..303C. doi:10.1007/bf02551274. S2CID 3958369. Archived from the original (PDF) on 10 October 2015.
Hornik, Kurt (1991). "Approximation Capabilities of Multilayer Feedforward Networks". Neural Networks. 4 (2): 251–257. doi:10.1016/0893-6080(91)90009-t. S2CID 7343126.
Orhan, A. E.; Ma, W. J. (2017). "Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback". Nature Communications. 8 (1): 138. Bibcode:2017NatCo...8..138O. doi:10.1038/s41467-017-00181-8. PMC 5527101. PMID 28743932.
Deng, L.; Yu, D. (2014). "Deep Learning: Methods and Applications" (PDF). Foundations and Trends in Signal Processing. 7 (3–4): 1–199. doi:10.1561/2000000039. Archived (PDF) from the original on 2016-03-14. Retrieved 2014-10-18.
Fukushima, K. (1969). "Visual feature extraction by a multilayered network of analog threshold elements". IEEE Transactions on Systems Science and Cybernetics. 5 (4): 322–333. doi:10.1109/TSSC.1969.300225.
Sonoda, Sho; Murata, Noboru (2017). "Neural network with unbounded activation functions is universal approximator". Applied and Computational Harmonic Analysis. 43 (2): 233–268. arXiv:1505.03654. doi:10.1016/j.acha.2015.12.005. S2CID 12149203.
Brush, Stephen G. (1967). "History of the Lenz-Ising Model". Reviews of Modern Physics. 39 (4): 883–893. Bibcode:1967RvMP...39..883B. doi:10.1103/RevModPhys.39.883.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554. PMC 346238. PMID 6953413.
Nakano, Kaoru (1971). "Learning Process in a Model of Associative Memory". Pattern Recognition and Machine Learning. pp. 172–186. doi:10.1007/978-1-4615-7566-5_15. ISBN 978-1-4615-7568-9.
Nakano, Kaoru (1972). "Associatron-A Model of Associative Memory". IEEE Transactions on Systems, Man, and Cybernetics. SMC-2 (3): 380–388. doi:10.1109/TSMC.1972.4309133.
Rosenblatt, F. (1958). "The perceptron: A probabilistic model for information storage and organization in the brain". Psychological Review. 65 (6): 386–408. doi:10.1037/h0042519. ISSN 1939-1471. PMID 13602029.
Ivakhnenko, A.G. (March 1970). "Heuristic self-organization in problems of engineering cybernetics". Automatica. 6 (2): 207–219. doi:10.1016/0005-1098(70)90092-0.
Ivakhnenko, Alexey (1971). "Polynomial theory of complex systems" (PDF). IEEE Transactions on Systems, Man, and Cybernetics. SMC-1 (4): 364–378. doi:10.1109/TSMC.1971.4308320. Archived (PDF) from the original on 2017-08-29. Retrieved 2019-11-05.
Robbins, H.; Monro, S. (1951). "A Stochastic Approximation Method". The Annals of Mathematical Statistics. 22 (3): 400. doi:10.1214/aoms/1177729586.
Fukushima, K. (1979). "Neural network model for a mechanism of pattern recognition unaffected by shift in position—Neocognitron". Trans. IECE (In Japanese). J62-A (10): 658–665. doi:10.1007/bf00344251. PMID 7370364. S2CID 206775608.
Fukushima, K. (1980). "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position". Biol. Cybern. 36 (4): 193–202. doi:10.1007/bf00344251. PMID 7370364. S2CID 206775608.
Kelley, Henry J. (1960). "Gradient theory of optimal flight paths". ARS Journal. 30 (10): 947–954. doi:10.2514/8.5282.
Linnainmaa, Seppo (1976). "Taylor expansion of the accumulated rounding error". BIT Numerical Mathematics. 16 (2): 146–160. doi:10.1007/bf01931367. S2CID 122357351.
Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (October 1986). "Learning representations by back-propagating errors". Nature. 323 (6088): 533–536. Bibcode:1986Natur.323..533R. doi:10.1038/323533a0. ISSN 1476-4687.
Zhang, Wei (1990). "Parallel distributed processing model with local space-invariant interconnections and its optical architecture". Applied Optics. 29 (32): 4790–7. Bibcode:1990ApOpt..29.4790Z. doi:10.1364/AO.29.004790. PMID 20577468.
Zhang, Wei (1991). "Image processing of human corneal endothelium based on a learning network". Applied Optics. 30 (29): 4211–7. Bibcode:1991ApOpt..30.4211Z. doi:10.1364/AO.30.004211. PMID 20706526.
Zhang, Wei (1994). "Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network". Medical Physics. 21 (4): 517–24. Bibcode:1994MedPh..21..517Z. doi:10.1118/1.597177. PMID 8058017.
LeCun, Yann; Léon Bottou; Yoshua Bengio; Patrick Haffner (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE. 86 (11): 2278–2324. CiteSeerX 10.1.1.32.9552. doi:10.1109/5.726791. S2CID 14542261. Retrieved October 7, 2016.
Elman, Jeffrey L. (March 1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. doi:10.1207/s15516709cog1402_1. ISSN 0364-0213.
Schmidhuber, Jürgen (1992). "Learning complex, extended sequences using the principle of history compression (based on TR FKI-148, 1991)" (PDF). Neural Computation. 4 (2): 234–242. doi:10.1162/neco.1992.4.2.234. S2CID 18271205.
Gers, Felix; Schmidhuber, Jürgen; Cummins, Fred (1999). "Learning to forget: Continual prediction with LSTM". 9th International Conference on Artificial Neural Networks: ICANN '99. Vol. 1999. pp. 850–855. doi:10.1049/cp:19991218. ISBN 0-85296-721-7.
Schmidhuber, Jürgen (2010). "Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990-2010)". IEEE Transactions on Autonomous Mental Development. 2 (3): 230–247. doi:10.1109/TAMD.2010.2056368. S2CID 234198.
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks. 127: 58–66. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008. PMID 32334341. S2CID 216056336.
Ackley, David H.; Hinton, Geoffrey E.; Sejnowski, Terrence J. (1985-01-01). "A learning algorithm for boltzmann machines". Cognitive Science. 9 (1): 147–169. doi:10.1016/S0364-0213(85)80012-4. ISSN 0364-0213.
Peter, Dayan; Hinton, Geoffrey E.; Neal, Radford M.; Zemel, Richard S. (1995). "The Helmholtz machine". Neural Computation. 7 (5): 889–904. doi:10.1162/neco.1995.7.5.889. hdl:21.11116/0000-0002-D6D3-E. PMID 7584891. S2CID 1890561.
Hinton, Geoffrey E.; Dayan, Peter; Frey, Brendan J.; Neal, Radford (1995-05-26). "The wake-sleep algorithm for unsupervised neural networks". Science. 268 (5214): 1158–1161. Bibcode:1995Sci...268.1158H. doi:10.1126/science.7761831. PMID 7761831. S2CID 871473.
Qian, Ning; Sejnowski, Terrence J. (1988-08-20). "Predicting the secondary structure of globular proteins using neural network models". Journal of Molecular Biology. 202 (4): 865–884. doi:10.1016/0022-2836(88)90564-5. ISSN 0022-2836. PMID 3172241.
Morgan, Nelson; Bourlard, Hervé; Renals, Steve; Cohen, Michael; Franco, Horacio (1 August 1993). "Hybrid neural network/hidden markov model systems for continuous speech recognition". International Journal of Pattern Recognition and Artificial Intelligence. 07 (4): 899–916. doi:10.1142/s0218001493000455. ISSN 0218-0014.
Waibel, A.; Hanazawa, T.; Hinton, G.; Shikano, K.; Lang, K. J. (March 1989). "Phoneme recognition using time-delay neural networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 37 (3): 328–339. doi:10.1109/29.21701. hdl:10338.dmlcz/135496. ISSN 0096-3518. S2CID 9563026. Archived (PDF) from the original on 2021-04-27. Retrieved 2019-09-24.
Baker, J.; Deng, Li; Glass, Jim; Khudanpur, S.; Lee, C.-H.; Morgan, N.; O'Shaughnessy, D. (2009). "Research Developments and Directions in Speech Recognition and Understanding, Part 1". IEEE Signal Processing Magazine. 26 (3): 75–80. Bibcode:2009ISPM...26...75B. doi:10.1109/msp.2009.932166. hdl:1721.1/51891. S2CID 357467.
Deng, L.; Hassanein, K.; Elmasry, M. (1994). "Analysis of correlation structure for a neural predictive model with applications to speech recognition". Neural Networks. 7 (2): 331–339. doi:10.1016/0893-6080(94)90027-2.
Doddington, G.; Przybocki, M.; Martin, A.; Reynolds, D. (2000). "The NIST speaker recognition evaluation ± Overview, methodology, systems, results, perspective". Speech Communication. 31 (2): 225–254. doi:10.1016/S0167-6393(99)00080-1.
Heck, L.; Konig, Y.; Sonmez, M.; Weintraub, M. (2000). "Robustness to Telephone Handset Distortion in Speaker Recognition by Discriminative Feature Design". Speech Communication. 31 (2): 181–192. doi:10.1016/s0167-6393(99)00077-1.
Hinton, Geoffrey E. (1 October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. ISSN 1364-6613. PMID 17921042. S2CID 15066318. Archived from the original on 11 October 2013. Retrieved 12 June 2017.
Hinton, G. E.; Osindero, S.; Teh, Y. W. (2006). "A Fast Learning Algorithm for Deep Belief Nets" (PDF). Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950. Archived (PDF) from the original on 2015-12-23. Retrieved 2011-07-20.
Hinton, Geoffrey E. (October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. PMID 17921042.
Hinton, Geoffrey E.; Osindero, Simon; Teh, Yee-Whye (July 2006). "A Fast Learning Algorithm for Deep Belief Nets". Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. ISSN 0899-7667. PMID 16764513.
Hinton, Geoffrey E. (2009-05-31). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947. ISSN 1941-6016.
Hinton, G.; Deng, L.; Yu, D.; Dahl, G.; Mohamed, A.; Jaitly, N.; Senior, A.; Vanhoucke, V.; Nguyen, P.; Sainath, T.; Kingsbury, B. (2012). "Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups". IEEE Signal Processing Magazine. 29 (6): 82–97. Bibcode:2012ISPM...29...82H. doi:10.1109/msp.2012.2205597. S2CID 206485943.
Seide, F.; Li, G.; Yu, D. (2011). "Conversational speech transcription using context-dependent deep neural networks". Interspeech 2011. pp. 437–440. doi:10.21437/Interspeech.2011-169. S2CID 398770. Archived from the original on 2017-10-12. Retrieved 2017-06-14.
Oh, K.-S.; Jung, K. (2004). "GPU implementation of neural networks". Pattern Recognition. 37 (6): 1311–1314. Bibcode:2004PatRe..37.1311O. doi:10.1016/j.patcog.2004.01.013.
Raina, Rajat; Madhavan, Anand; Ng, Andrew Y. (2009-06-14). "Large-scale deep unsupervised learning using graphics processors". Proceedings of the 26th Annual International Conference on Machine Learning. ICML '09. New York, NY, USA: Association for Computing Machinery. pp. 873–880. doi:10.1145/1553374.1553486. ISBN 978-1-60558-516-1.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (21 September 2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation. 22 (12): 3207–3220. arXiv:1003.0358. doi:10.1162/neco_a_00052. ISSN 0899-7667. PMID 20858131. S2CID 1918673.
Ciresan, D. C.; Meier, U.; Masci, J.; Gambardella, L.M.; Schmidhuber, J. (2011). "Flexible, High Performance Convolutional Neural Networks for Image Classification" (PDF). International Joint Conference on Artificial Intelligence. doi:10.5591/978-1-57735-516-8/ijcai11-210. Archived (PDF) from the original on 2014-09-29. Retrieved 2017-06-13.
Ciresan, D.; Giusti, A.; Gambardella, L.M.; Schmidhuber, J. (2013). "Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks". Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. Lecture Notes in Computer Science. Vol. 7908. pp. 411–418. doi:10.1007/978-3-642-40763-5_51. ISBN 978-3-642-38708-1. PMID 24579167.
He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian (2016). Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA: IEEE. pp. 770–778. arXiv:1512.03385. doi:10.1109/CVPR.2016.90. ISBN 978-1-4673-8851-1.
Singh, Premjeet; Saha, Goutam; Sahidullah, Md (2021). "Non-linear frequency warping using constant-Q transformation for speech emotion recognition". 2021 International Conference on Computer Communication and Informatics (ICCCI). pp. 1–4. arXiv:2102.04029. doi:10.1109/ICCCI50826.2021.9402569. ISBN 978-1-7281-5875-4. S2CID 231846518.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042. S2CID 515925.
Kumar, Nishant; Raubal, Martin (2021). "Applications of deep learning in congestion detection, prediction and alleviation: A survey". Transportation Research Part C: Emerging Technologies. 133: 103432. arXiv:2102.09759. Bibcode:2021TRPC..13303432K. doi:10.1016/j.trc.2021.103432. hdl:10230/42143. S2CID 240420107.
Gers, Felix A.; Schmidhuber, Jürgen (2001). "LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages". IEEE Transactions on Neural Networks. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962. S2CID 10192330. Archived from the original on 2020-01-26. Retrieved 2020-02-25.
Mikolov, T.; et al. (2010). "Recurrent neural network based language model" (PDF). Interspeech: 1045–1048. doi:10.21437/Interspeech.2010-343. S2CID 17048224. Archived (PDF) from the original on 2017-05-16. Retrieved 2017-06-13.
Hochreiter, Sepp; Schmidhuber, Jürgen (1 November 1997). "Long Short-Term Memory". Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276. S2CID 1915014.
LeCun, Y.; et al. (1998). "Gradient-based learning applied to document recognition". Proceedings of the IEEE. 86 (11): 2278–2324. doi:10.1109/5.726791. S2CID 14542261.
Sainath, Tara N.; Mohamed, Abdel-Rahman; Kingsbury, Brian; Ramabhadran, Bhuvana (2013). "Deep convolutional neural networks for LVCSR". 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 8614–8618. doi:10.1109/icassp.2013.6639347. ISBN 978-1-4799-0356-6. S2CID 13816461.
Bengio, Yoshua; Boulanger-Lewandowski, Nicolas; Pascanu, Razvan (2013). "Advances in optimizing recurrent networks". 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 8624–8628. arXiv:1212.0901. CiteSeerX 10.1.1.752.9151. doi:10.1109/icassp.2013.6639349. ISBN 978-1-4799-0356-6. S2CID 12485056.
Kumar, Nishant; Martin, Henry; Raubal, Martin (2024). "Enhancing Deep Learning-Based City-Wide Traffic Prediction Pipelines Through Complexity Analysis". Data Science for Transportation. 6 (3): Article 24. doi:10.1007/s42421-024-00109-x.
You, Yang; Buluç, Aydın; Demmel, James (November 2017). "Scaling deep learning on GPU and knights landing clusters". Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17. SC '17, ACM. pp. 1–12. doi:10.1145/3126908.3126912. ISBN 9781450351140. S2CID 8869270. Archived from the original on 29 July 2020. Retrieved 5 March 2018.
Viebke, André; Memeti, Suejb; Pllana, Sabri; Abraham, Ajith (2019). "CHAOS: a parallelization scheme for training convolutional neural networks on Intel Xeon Phi". The Journal of Supercomputing. 75: 197–227. arXiv:1702.07908. Bibcode:2017arXiv170207908V. doi:10.1007/s11227-017-1994-x. S2CID 14135321.
P, JouppiNorman; YoungCliff; PatilNishant; PattersonDavid; AgrawalGaurav; BajwaRaminder; BatesSarah; BhatiaSuresh; BodenNan; BorchersAl; BoyleRick (2017-06-24). "In-Datacenter Performance Analysis of a Tensor Processing Unit". ACM SIGARCH Computer Architecture News. 45 (2): 1–12. arXiv:1704.04760. doi:10.1145/3140659.3080246.
Marega, Guilherme Migliato; Zhao, Yanfei; Avsar, Ahmet; Wang, Zhenyu; Tripati, Mukesh; Radenovic, Aleksandra; Kis, Anras (2020). "Logic-in-memory based on an atomically thin semiconductor". Nature. 587 (2): 72–77. Bibcode:2020Natur.587...72M. doi:10.1038/s41586-020-2861-0. PMC 7116757. PMID 33149289.
Feldmann, J.; Youngblood, N.; Karpov, M.; et al. (2021). "Parallel convolutional processing using an integrated photonic tensor". Nature. 589 (2): 52–58. arXiv:2002.00281. doi:10.1038/s41586-020-03070-1. PMID 33408373. S2CID 211010976.
Garofolo, J.S.; Lamel, L.F.; Fisher, W.M.; Fiscus, J.G.; Pallett, D.S.; Dahlgren, N.L.; Zue, V. (1993). TIMIT Acoustic-Phonetic Continuous Speech Corpus. Linguistic Data Consortium. doi:10.35111/17gk-bn40. ISBN 1-58563-019-5. Retrieved 27 December 2023.
Robinson, Tony (30 September 1991). "Several Improvements to a Recurrent Error Propagation Network Phone Recognition System". Cambridge University Engineering Department Technical Report. CUED/F-INFENG/TR82. doi:10.13140/RG.2.2.15418.90567.
Abdel-Hamid, O.; et al. (2014). "Convolutional Neural Networks for Speech Recognition". IEEE/ACM Transactions on Audio, Speech, and Language Processing. 22 (10): 1533–1545. doi:10.1109/taslp.2014.2339736. S2CID 206602362. Archived from the original on 2020-09-22. Retrieved 2018-04-20.
Deng, L.; Platt, J. (2014). "Ensemble Deep Learning for Speech Recognition". Proc. Interspeech: 1915–1919. doi:10.21437/Interspeech.2014-433. S2CID 15641618.
Tóth, Laszló (2015). "Phone Recognition with Hierarchical Convolutional Deep Maxout Networks" (PDF). EURASIP Journal on Audio, Speech, and Music Processing. 2015. doi:10.1186/s13636-015-0068-3. S2CID 217950236. Archived (PDF) from the original on 2020-09-24. Retrieved 2019-04-01.
Cireşan, Dan; Meier, Ueli; Masci, Jonathan; Schmidhuber, Jürgen (August 2012). "Multi-column deep neural network for traffic sign classification". Neural Networks. Selected Papers from IJCNN 2011. 32: 333–338. CiteSeerX 10.1.1.226.8219. doi:10.1016/j.neunet.2012.02.023. PMID 22386783.
G. W. Smith; Frederic Fol Leymarie (10 April 2017). "The Machine as Artist: An Introduction". Arts. 6 (4): 5. doi:10.3390/arts6020005.
Blaise Agüera y Arcas (29 September 2017). "Art in the Age of Machine Intelligence". Arts. 6 (4): 18. doi:10.3390/arts6040018.
Socher, R.; Perelygin, A.; Wu, J.; Chuang, J.; Manning, C.D.; Ng, A.; Potts, C. (October 2013). "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank" (PDF). Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics: 1631–1642. doi:10.18653/v1/D13-1170. Archived (PDF) from the original on 28 December 2016. Retrieved 21 December 2023.
Mesnil, G.; Dauphin, Y.; Yao, K.; Bengio, Y.; Deng, L.; Hakkani-Tur, D.; He, X.; Heck, L.; Tur, G.; Yu, D.; Zweig, G. (2015). "Using recurrent neural networks for slot filling in spoken language understanding". IEEE Transactions on Audio, Speech, and Language Processing. 23 (3): 530–539. doi:10.1109/taslp.2014.2383614. S2CID 1317136.
Brocardo, Marcelo Luiz; Traore, Issa; Woungang, Isaac; Obaidat, Mohammad S. (2017). "Authorship verification using deep belief network systems". International Journal of Communication Systems. 30 (12): e3259. doi:10.1002/dac.3259. S2CID 40745740.
Kariampuzha, William; Alyea, Gioconda; Qu, Sue; Sanjak, Jaleal; Mathé, Ewy; Sid, Eric; Chatelaine, Haley; Yadaw, Arjun; Xu, Yanji; Zhu, Qian (2023). "Precision information extraction for rare disease epidemiology at scale". Journal of Translational Medicine. 21 (1): 157. doi:10.1186/s12967-023-04011-y. PMC 9972634. PMID 36855134.
Arrowsmith, J; Miller, P (2013). "Trial watch: Phase II and phase III attrition rates 2011-2012". Nature Reviews Drug Discovery. 12 (8): 569. doi:10.1038/nrd4090. PMID 23903212. S2CID 20246434.
Verbist, B; Klambauer, G; Vervoort, L; Talloen, W; The Qstar, Consortium; Shkedy, Z; Thas, O; Bender, A; Göhlmann, H. W.; Hochreiter, S (2015). "Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project". Drug Discovery Today. 20 (5): 505–513. doi:10.1016/j.drudis.2014.12.014. hdl:1942/18723. PMID 25582842.
Zhavoronkov, Alex (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors". Nature Biotechnology. 37 (9): 1038–1040. doi:10.1038/s41587-019-0224-x. PMID 31477924. S2CID 201716327.
Feng, X.Y.; Zhang, H.; Ren, Y.J.; Shang, P.H.; Zhu, Y.; Liang, Y.C.; Guan, R.C.; Xu, D. (2019). "The Deep Learning–Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study". Journal of Medical Internet Research. 21 (5): e12957. doi:10.2196/12957. PMC 6555124. PMID 31127715.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (1 January 2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM. pp. 533–540. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210. Archived from the original on 9 May 2021. Retrieved 23 November 2015.
Sathyanarayana, Aarti (1 January 2016). "Sleep Quality Prediction From Wearable Data Using Deep Learning". JMIR mHealth and uHealth. 4 (4): e125. doi:10.2196/mhealth.6562. PMC 5116102. PMID 27815231. S2CID 3821594.
Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (13 August 2016). "Using recurrent neural network models for early detection of heart failure onset". Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725. PMID 27521897.
Shalev, Y.; Painsky, A.; Ben-Gal, I. (2022). "Neural Joint Entropy Estimation" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (4): 5488–5500. arXiv:2012.11197. doi:10.1109/TNNLS.2022.3204919. PMID 36155469. S2CID 229339809.
Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (December 2017). "A survey on deep learning in medical image analysis". Medical Image Analysis. 42: 60–88. arXiv:1702.05747. Bibcode:2017arXiv170205747L. doi:10.1016/j.media.2017.07.005. PMID 28778026. S2CID 2088679.
Forslid, Gustav; Wieslander, Hakan; Bengtsson, Ewert; Wahlby, Carolina; Hirsch, Jan-Michael; Stark, Christina Runow; Sadanandan, Sajith Kecheril (2017). "Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy". 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). pp. 82–89. doi:10.1109/ICCVW.2017.18. ISBN 9781538610343. S2CID 4728736. Archived from the original on 2021-05-09. Retrieved 2019-11-12.
Dong, Xin; Zhou, Yizhao; Wang, Lantian; Peng, Jingfeng; Lou, Yanbo; Fan, Yiqun (2020). "Liver Cancer Detection Using Hybridized Fully Convolutional Neural Network Based on Deep Learning Framework". IEEE Access. 8: 129889–129898. Bibcode:2020IEEEA...8l9889D. doi:10.1109/ACCESS.2020.3006362. ISSN 2169-3536. S2CID 220733699.
Lyakhov, Pavel Alekseevich; Lyakhova, Ulyana Alekseevna; Nagornov, Nikolay Nikolaevich (2022-04-03). "System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of Heterogeneous Data Based on a Multimodal Neural Network". Cancers. 14 (7): 1819. doi:10.3390/cancers14071819. ISSN 2072-6694. PMC 8997449. PMID 35406591.
De, Shaunak; Maity, Abhishek; Goel, Vritti; Shitole, Sanjay; Bhattacharya, Avik (2017). "Predicting the popularity of instagram posts for a lifestyle magazine using deep learning". 2017 2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA). pp. 174–177. doi:10.1109/CSCITA.2017.8066548. ISBN 978-1-5090-4381-1. S2CID 35350962.
Kleanthous, Christos; Chatzis, Sotirios (2020). "Gated Mixture Variational Autoencoders for Value Added Tax audit case selection". Knowledge-Based Systems. 188: 105048. doi:10.1016/j.knosys.2019.105048. S2CID 204092079.
Merchant, Amil; Batzner, Simon; Schoenholz, Samuel S.; Aykol, Muratahan; Cheon, Gowoon; Cubuk, Ekin Dogus (December 2023). "Scaling deep learning for materials discovery". Nature. 624 (7990): 80–85. Bibcode:2023Natur.624...80M. doi:10.1038/s41586-023-06735-9. ISSN 1476-4687. PMC 10700131. PMID 38030720.
Peplow, Mark (2023-11-29). "Google AI and robots join forces to build new materials". Nature. doi:10.1038/d41586-023-03745-5. PMID 38030771. S2CID 265503872.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Han, J.; Jentzen, A.; E, W. (2018). "Solving high-dimensional partial differential equations using deep learning". Proceedings of the National Academy of Sciences. 115 (34): 8505–8510. arXiv:1707.02568. Bibcode:2018PNAS..115.8505H. doi:10.1073/pnas.1718942115. PMC 6112690. PMID 30082389.
Oktem, Figen S.; Kar, Oğuzhan Fatih; Bezek, Can Deniz; Kamalabadi, Farzad (2021). "High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction". IEEE Transactions on Computational Imaging. 7: 489–504. arXiv:2008.11625. doi:10.1109/TCI.2021.3075349. ISSN 2333-9403. S2CID 235340737.
Bernhardt, Melanie; Vishnevskiy, Valery; Rau, Richard; Goksel, Orcun (December 2020). "Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67 (12): 2584–2594. arXiv:2006.14395. doi:10.1109/TUFFC.2020.3010186. ISSN 1525-8955. PMID 32746211. S2CID 220055785.
Lam, Remi; Sanchez-Gonzalez, Alvaro; Willson, Matthew; Wirnsberger, Peter; Fortunato, Meire; Alet, Ferran; Ravuri, Suman; Ewalds, Timo; Eaton-Rosen, Zach; Hu, Weihua; Merose, Alexander; Hoyer, Stephan; Holland, George; Vinyals, Oriol; Stott, Jacklynn (2023-12-22). "Learning skillful medium-range global weather forecasting". Science. 382 (6677): 1416–1421. arXiv:2212.12794. Bibcode:2023Sci...382.1416L. doi:10.1126/science.adi2336. ISSN 0036-8075. PMID 37962497.
Galkin, F.; Mamoshina, P.; Kochetov, K.; Sidorenko, D.; Zhavoronkov, A. (2020). "DeepMAge: A Methylation Aging Clock Developed with Deep Learning". Aging and Disease. doi:10.14336/AD.
Utgoff, P. E.; Stracuzzi, D. J. (2002). "Many-layered learning". Neural Computation. 14 (10): 2497–2529. doi:10.1162/08997660260293319. PMID 12396572. S2CID 1119517.
Shrager, J.; Johnson, MH (1996). "Dynamic plasticity influences the emergence of function in a simple cortical array". Neural Networks. 9 (7): 1119–1129. doi:10.1016/0893-6080(96)00033-0. PMID 12662587.
Quartz, SR; Sejnowski, TJ (1997). "The neural basis of cognitive development: A constructivist manifesto". Behavioral and Brain Sciences. 20 (4): 537–556. CiteSeerX 10.1.1.41.7854. doi:10.1017/s0140525x97001581. PMID 10097006. S2CID 5818342.
Mazzoni, P.; Andersen, R. A.; Jordan, M. I. (15 May 1991). "A more biologically plausible learning rule for neural networks". Proceedings of the National Academy of Sciences. 88 (10): 4433–4437. Bibcode:1991PNAS...88.4433M. doi:10.1073/pnas.88.10.4433. ISSN 0027-8424. PMC 51674. PMID 1903542.
O'Reilly, Randall C. (1 July 1996). "Biologically Plausible Error-Driven Learning Using Local Activation Differences: The Generalized Recirculation Algorithm". Neural Computation. 8 (5): 895–938. doi:10.1162/neco.1996.8.5.895. ISSN 0899-7667. S2CID 2376781.
Testolin, Alberto; Zorzi, Marco (2016). "Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions". Frontiers in Computational Neuroscience. 10: 73. doi:10.3389/fncom.2016.00073. ISSN 1662-5188. PMC 4943066. PMID 27468262. S2CID 9868901.
Testolin, Alberto; Stoianov, Ivilin; Zorzi, Marco (September 2017). "Letter perception emerges from unsupervised deep learning and recycling of natural image features". Nature Human Behaviour. 1 (9): 657–664. doi:10.1038/s41562-017-0186-2. ISSN 2397-3374. PMID 31024135. S2CID 24504018.
Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS Computational Biology. 7 (11): e1002211. Bibcode:2011PLSCB...7E2211B. doi:10.1371/journal.pcbi.1002211. ISSN 1553-7358. PMC 3207943. PMID 22096452. S2CID 7504633.
Cash, S.; Yuste, R. (February 1999). "Linear summation of excitatory inputs by CA1 pyramidal neurons". Neuron. 22 (2): 383–394. doi:10.1016/s0896-6273(00)81098-3. ISSN 0896-6273. PMID 10069343. S2CID 14663106.
Olshausen, B; Field, D (1 August 2004). "Sparse coding of sensory inputs". Current Opinion in Neurobiology. 14 (4): 481–487. doi:10.1016/j.conb.2004.07.007. ISSN 0959-4388. PMID 15321069. S2CID 16560320.
Yamins, Daniel L K; DiCarlo, James J (March 2016). "Using goal-driven deep learning models to understand sensory cortex". Nature Neuroscience. 19 (3): 356–365. doi:10.1038/nn.4244. ISSN 1546-1726. PMID 26906502. S2CID 16970545.
Zorzi, Marco; Testolin, Alberto (19 February 2018). "An emergentist perspective on the origin of number sense". Phil. Trans. R. Soc. B. 373 (1740): 20170043. doi:10.1098/rstb.2017.0043. ISSN 0962-8436. PMC 5784047. PMID 29292348. S2CID 39281431.
Güçlü, Umut; van Gerven, Marcel A. J. (8 July 2015). "Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream". Journal of Neuroscience. 35 (27): 10005–10014. arXiv:1411.6422. doi:10.1523/jneurosci.5023-14.2015. PMC 6605414. PMID 26157000.
Gibney, Elizabeth (2016). "Google AI algorithm masters ancient game of Go". Nature. 529 (7587): 445–446. Bibcode:2016Natur.529..445G. doi:10.1038/529445a. PMID 26819021. S2CID 4460235.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Bradley Knox, W.; Stone, Peter (2008). "TAMER: Training an Agent Manually via Evaluative Reinforcement". 2008 7th IEEE International Conference on Development and Learning. pp. 292–297. doi:10.1109/devlrn.2008.4640845. ISBN 978-1-4244-2661-4. S2CID 5613334.
Zhu, S.C.; Mumford, D. (2006). "A stochastic grammar of images". Found. Trends Comput. Graph. Vis. 2 (4): 259–362. CiteSeerX 10.1.1.681.2190. doi:10.1561/0600000018.
Gibney, Elizabeth (2017). "The scientist who spots fake videos". Nature. doi:10.1038/nature.2017.22784. Archived from the original on 2017-10-10. Retrieved 2017-10-11.
Mühlhoff, Rainer (6 November 2019). "Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning". New Media & Society. 22 (10): 1868–1884. doi:10.1177/1461444819885334. ISSN 1461-4448. S2CID 209363848.

dx.doi.org

Qian, Ning; Sejnowski, Terrence J. (1988-08-20). "Predicting the secondary structure of globular proteins using neural network models". Journal of Molecular Biology. 202 (4): 865–884. doi:10.1016/0022-2836(88)90564-5. ISSN 0022-2836. PMID 3172241.

drive.google.com

Zhang, Wei (1988). "Shift-invariant pattern recognition neural network and its optical architecture". Proceedings of Annual Conference of the Japan Society of Applied Physics.
Zhang, Wei (1990). "Parallel distributed processing model with local space-invariant interconnections and its optical architecture". Applied Optics. 29 (32): 4790–7. Bibcode:1990ApOpt..29.4790Z. doi:10.1364/AO.29.004790. PMID 20577468.
Zhang, Wei (1991). "Image processing of human corneal endothelium based on a learning network". Applied Optics. 30 (29): 4211–7. Bibcode:1991ApOpt..30.4211Z. doi:10.1364/AO.30.004211. PMID 20706526.
Zhang, Wei (1994). "Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network". Medical Physics. 21 (4): 517–24. Bibcode:1994MedPh..21..517Z. doi:10.1118/1.597177. PMID 8058017.

dtic.mil

apps.dtic.mil

Rumelhart, David E., Geoffrey E. Hinton, and R. J. Williams. "Learning Internal Representations by Error Propagation Archived 2022-10-13 at the Wayback Machine". David E. Rumelhart, James L. McClelland, and the PDP research group. (editors), Parallel distributed processing: Explorations in the microstructure of cognition, Volume 1: Foundation. MIT Press, 1986.

elsevier.com

linkinghub.elsevier.com

Ivakhnenko, A.G. (March 1970). "Heuristic self-organization in problems of engineering cybernetics". Automatica. 6 (2): 207–219. doi:10.1016/0005-1098(70)90092-0.
Hinton, Geoffrey E. (October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. PMID 17921042.

escholarship.org

Jordan, Michael I. (1986). "Attractor dynamics and parallelism in a connectionist sequential machine". Proceedings of the Annual Meeting of the Cognitive Science Society. 8.
You, Yang; Buluç, Aydın; Demmel, James (November 2017). "Scaling deep learning on GPU and knights landing clusters". Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17. SC '17, ACM. pp. 1–12. doi:10.1145/3126908.3126912. ISBN 9781450351140. S2CID 8869270. Archived from the original on 29 July 2020. Retrieved 5 March 2018.

eurekalert.org

"Army researchers develop new algorithms to train robots". EurekAlert!. Archived from the original on 28 August 2018. Retrieved 29 August 2018.

floydhub.com

blog.floydhub.com

"Colorizing and Restoring Old Images with Deep Learning". FloydHub Blog. 13 November 2018. Archived from the original on 11 October 2019. Retrieved 11 October 2019.

gizmodo.com

"Hackers Have Already Started to Weaponize Artificial Intelligence". Gizmodo. 11 September 2017. Archived from the original on 11 October 2019. Retrieved 11 October 2019.

globalbankingandfinance.com

Czech, Tomasz (28 June 2018). "Deep learning: the next frontier for money laundering detection". Global Banking and Finance Review. Archived from the original on 2018-11-16. Retrieved 2018-07-15.

gmdh.net

Ivakhnenko, Alexey (1971). "Polynomial theory of complex systems" (PDF). IEEE Transactions on Systems, Man, and Cybernetics. SMC-1 (4): 364–378. doi:10.1109/TSMC.1971.4308320. Archived (PDF) from the original on 2017-08-29. Retrieved 2019-11-05.

goertzel.org

Goertzel, Ben (2015). "Are there Deep Reasons Underlying the Pathologies of Today's Deep Learning Algorithms?" (PDF). Archived (PDF) from the original on 2015-05-13. Retrieved 2015-05-10.

googleblog.com

research.googleblog.com

Schuster, Mike; Johnson, Melvin; Thorat, Nikhil (22 November 2016). "Zero-Shot Translation with Google's Multilingual Neural Machine Translation System". Google Research Blog. Archived from the original on 10 July 2017. Retrieved 23 March 2017.

googleresearch.blogspot.ch

Sak, Haşim; Senior, Andrew; Rao, Kanishka; Beaufays, Françoise; Schalkwyk, Johan (September 2015). "Google voice search: faster and more accurate". Archived from the original on 2016-03-09. Retrieved 2016-04-09.

googleresearch.blogspot.co.at

Google Research Blog. The neural networks behind Google Voice transcription. August 11, 2015. By Françoise Beaufays http://googleresearch.blogspot.co.at/2015/08/the-neural-networks-behind-google-voice.html

googleresearch.blogspot.co.uk

Alexander Mordvintsev; Christopher Olah; Mike Tyka (17 June 2015). "Inceptionism: Going Deeper into Neural Networks". Google Research Blog. Archived from the original on 3 July 2015. Retrieved 20 June 2015.

googleusercontent.com

static.googleusercontent.com

Szegedy, Christian (2015). "Going deeper with convolutions" (PDF). Cvpr2015. arXiv:1409.4842.
Sak, Hasim; Senior, Andrew; Beaufays, Francoise (2014). "Long Short-Term Memory recurrent neural network architectures for large scale acoustic modeling" (PDF). Archived from the original (PDF) on 24 April 2018.
Zen, Heiga; Sak, Hasim (2015). "Unidirectional Long Short-Term Memory Recurrent Neural Network with Recurrent Output Layer for Low-Latency Speech Synthesis" (PDF). Google.com. ICASSP. pp. 4470–4474. Archived (PDF) from the original on 2021-05-09. Retrieved 2017-06-13.

governmentciomedia.com

"Talk to the Algorithms: AI Becomes a Faster Learner". governmentciomedia.com. 16 May 2018. Archived from the original on 28 August 2018. Retrieved 29 August 2018.

hal.science

LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep Learning" (PDF). Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442. S2CID 3074096.
Tubaro, Paola (2020). "Whose intelligence is artificial intelligence?". Global Dialogue: 38–39.

handle.net

hdl.handle.net

Peter, Dayan; Hinton, Geoffrey E.; Neal, Radford M.; Zemel, Richard S. (1995). "The Helmholtz machine". Neural Computation. 7 (5): 889–904. doi:10.1162/neco.1995.7.5.889. hdl:21.11116/0000-0002-D6D3-E. PMID 7584891. S2CID 1890561.
Waibel, A.; Hanazawa, T.; Hinton, G.; Shikano, K.; Lang, K. J. (March 1989). "Phoneme recognition using time-delay neural networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 37 (3): 328–339. doi:10.1109/29.21701. hdl:10338.dmlcz/135496. ISSN 0096-3518. S2CID 9563026. Archived (PDF) from the original on 2021-04-27. Retrieved 2019-09-24.
Baker, J.; Deng, Li; Glass, Jim; Khudanpur, S.; Lee, C.-H.; Morgan, N.; O'Shaughnessy, D. (2009). "Research Developments and Directions in Speech Recognition and Understanding, Part 1". IEEE Signal Processing Magazine. 26 (3): 75–80. Bibcode:2009ISPM...26...75B. doi:10.1109/msp.2009.932166. hdl:1721.1/51891. S2CID 357467.
Kumar, Nishant; Raubal, Martin (2021). "Applications of deep learning in congestion detection, prediction and alleviation: A survey". Transportation Research Part C: Emerging Technologies. 133: 103432. arXiv:2102.09759. Bibcode:2021TRPC..13303432K. doi:10.1016/j.trc.2021.103432. hdl:10230/42143. S2CID 240420107.
Verbist, B; Klambauer, G; Vervoort, L; Talloen, W; The Qstar, Consortium; Shkedy, Z; Thas, O; Bender, A; Göhlmann, H. W.; Hochreiter, S (2015). "Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project". Drug Discovery Today. 20 (5): 505–513. doi:10.1016/j.drudis.2014.12.014. hdl:1942/18723. PMID 25582842.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (1 January 2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM. pp. 533–540. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210. Archived from the original on 9 May 2021. Retrieved 23 November 2015.

harvard.edu

ui.adsabs.harvard.edu

LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep Learning" (PDF). Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442. S2CID 3074096.
Hinton, G.E. (2009). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947.
Cybenko (1989). "Approximations by superpositions of sigmoidal functions" (PDF). Mathematics of Control, Signals, and Systems. 2 (4): 303–314. Bibcode:1989MCSS....2..303C. doi:10.1007/bf02551274. S2CID 3958369. Archived from the original (PDF) on 10 October 2015.
Orhan, A. E.; Ma, W. J. (2017). "Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback". Nature Communications. 8 (1): 138. Bibcode:2017NatCo...8..138O. doi:10.1038/s41467-017-00181-8. PMC 5527101. PMID 28743932.
Brush, Stephen G. (1967). "History of the Lenz-Ising Model". Reviews of Modern Physics. 39 (4): 883–893. Bibcode:1967RvMP...39..883B. doi:10.1103/RevModPhys.39.883.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554. PMC 346238. PMID 6953413.
Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (October 1986). "Learning representations by back-propagating errors". Nature. 323 (6088): 533–536. Bibcode:1986Natur.323..533R. doi:10.1038/323533a0. ISSN 1476-4687.
Zhang, Wei (1990). "Parallel distributed processing model with local space-invariant interconnections and its optical architecture". Applied Optics. 29 (32): 4790–7. Bibcode:1990ApOpt..29.4790Z. doi:10.1364/AO.29.004790. PMID 20577468.
Zhang, Wei (1991). "Image processing of human corneal endothelium based on a learning network". Applied Optics. 30 (29): 4211–7. Bibcode:1991ApOpt..30.4211Z. doi:10.1364/AO.30.004211. PMID 20706526.
Zhang, Wei (1994). "Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network". Medical Physics. 21 (4): 517–24. Bibcode:1994MedPh..21..517Z. doi:10.1118/1.597177. PMID 8058017.
Hinton, Geoffrey E.; Dayan, Peter; Frey, Brendan J.; Neal, Radford (1995-05-26). "The wake-sleep algorithm for unsupervised neural networks". Science. 268 (5214): 1158–1161. Bibcode:1995Sci...268.1158H. doi:10.1126/science.7761831. PMID 7761831. S2CID 871473.
Baker, J.; Deng, Li; Glass, Jim; Khudanpur, S.; Lee, C.-H.; Morgan, N.; O'Shaughnessy, D. (2009). "Research Developments and Directions in Speech Recognition and Understanding, Part 1". IEEE Signal Processing Magazine. 26 (3): 75–80. Bibcode:2009ISPM...26...75B. doi:10.1109/msp.2009.932166. hdl:1721.1/51891. S2CID 357467.
Hinton, Geoffrey E. (2009-05-31). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947. ISSN 1941-6016.
Hinton, G.; Deng, L.; Yu, D.; Dahl, G.; Mohamed, A.; Jaitly, N.; Senior, A.; Vanhoucke, V.; Nguyen, P.; Sainath, T.; Kingsbury, B. (2012). "Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups". IEEE Signal Processing Magazine. 29 (6): 82–97. Bibcode:2012ISPM...29...82H. doi:10.1109/msp.2012.2205597. S2CID 206485943.
Oh, K.-S.; Jung, K. (2004). "GPU implementation of neural networks". Pattern Recognition. 37 (6): 1311–1314. Bibcode:2004PatRe..37.1311O. doi:10.1016/j.patcog.2004.01.013.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042. S2CID 515925.
Kumar, Nishant; Raubal, Martin (2021). "Applications of deep learning in congestion detection, prediction and alleviation: A survey". Transportation Research Part C: Emerging Technologies. 133: 103432. arXiv:2102.09759. Bibcode:2021TRPC..13303432K. doi:10.1016/j.trc.2021.103432. hdl:10230/42143. S2CID 240420107.
Sutskever, L.; Vinyals, O.; Le, Q. (2014). "Sequence to Sequence Learning with Neural Networks" (PDF). Proc. NIPS. arXiv:1409.3215. Bibcode:2014arXiv1409.3215S. Archived (PDF) from the original on 2021-05-09. Retrieved 2017-06-13.
Viebke, André; Memeti, Suejb; Pllana, Sabri; Abraham, Ajith (2019). "CHAOS: a parallelization scheme for training convolutional neural networks on Intel Xeon Phi". The Journal of Supercomputing. 75: 197–227. arXiv:1702.07908. Bibcode:2017arXiv170207908V. doi:10.1007/s11227-017-1994-x. S2CID 14135321.
Marega, Guilherme Migliato; Zhao, Yanfei; Avsar, Ahmet; Wang, Zhenyu; Tripati, Mukesh; Radenovic, Aleksandra; Kis, Anras (2020). "Logic-in-memory based on an atomically thin semiconductor". Nature. 587 (2): 72–77. Bibcode:2020Natur.587...72M. doi:10.1038/s41586-020-2861-0. PMC 7116757. PMID 33149289.
Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (December 2017). "A survey on deep learning in medical image analysis". Medical Image Analysis. 42: 60–88. arXiv:1702.05747. Bibcode:2017arXiv170205747L. doi:10.1016/j.media.2017.07.005. PMID 28778026. S2CID 2088679.
Dong, Xin; Zhou, Yizhao; Wang, Lantian; Peng, Jingfeng; Lou, Yanbo; Fan, Yiqun (2020). "Liver Cancer Detection Using Hybridized Fully Convolutional Neural Network Based on Deep Learning Framework". IEEE Access. 8: 129889–129898. Bibcode:2020IEEEA...8l9889D. doi:10.1109/ACCESS.2020.3006362. ISSN 2169-3536. S2CID 220733699.
Merchant, Amil; Batzner, Simon; Schoenholz, Samuel S.; Aykol, Muratahan; Cheon, Gowoon; Cubuk, Ekin Dogus (December 2023). "Scaling deep learning for materials discovery". Nature. 624 (7990): 80–85. Bibcode:2023Natur.624...80M. doi:10.1038/s41586-023-06735-9. ISSN 1476-4687. PMC 10700131. PMID 38030720.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Han, J.; Jentzen, A.; E, W. (2018). "Solving high-dimensional partial differential equations using deep learning". Proceedings of the National Academy of Sciences. 115 (34): 8505–8510. arXiv:1707.02568. Bibcode:2018PNAS..115.8505H. doi:10.1073/pnas.1718942115. PMC 6112690. PMID 30082389.
Lam, Remi; Sanchez-Gonzalez, Alvaro; Willson, Matthew; Wirnsberger, Peter; Fortunato, Meire; Alet, Ferran; Ravuri, Suman; Ewalds, Timo; Eaton-Rosen, Zach; Hu, Weihua; Merose, Alexander; Hoyer, Stephan; Holland, George; Vinyals, Oriol; Stott, Jacklynn (2023-12-22). "Learning skillful medium-range global weather forecasting". Science. 382 (6677): 1416–1421. arXiv:2212.12794. Bibcode:2023Sci...382.1416L. doi:10.1126/science.adi2336. ISSN 0036-8075. PMID 37962497.
Mazzoni, P.; Andersen, R. A.; Jordan, M. I. (15 May 1991). "A more biologically plausible learning rule for neural networks". Proceedings of the National Academy of Sciences. 88 (10): 4433–4437. Bibcode:1991PNAS...88.4433M. doi:10.1073/pnas.88.10.4433. ISSN 0027-8424. PMC 51674. PMID 1903542.
Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS Computational Biology. 7 (11): e1002211. Bibcode:2011PLSCB...7E2211B. doi:10.1371/journal.pcbi.1002211. ISSN 1553-7358. PMC 3207943. PMID 22096452. S2CID 7504633.
Gibney, Elizabeth (2016). "Google AI algorithm masters ancient game of Go". Nature. 529 (7587): 445–446. Bibcode:2016Natur.529..445G. doi:10.1038/529445a. PMID 26819021. S2CID 4460235.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.

hs-augsburg.de

"bibliotheca Augustana". www.hs-augsburg.de.

huawei.com

consumer.huawei.com

"HUAWEI Reveals the Future of Mobile AI at IFA 2017 | HUAWEI Latest News | HUAWEI Global". consumer.huawei.com.

idsia.ch

people.idsia.ch

Schmidhuber, Juergen (25 Oct 2014). "Who Invented Backpropagation?". IDSIA, Switzerland. Archived from the original on 30 July 2024. Retrieved 14 Sep 2024.
Schmidhuber, Jürgen (April 1991). "Neural Sequence Chunkers" (PDF). TR FKI-148, TU Munich.
S. Hochreiter., "Untersuchungen zu dynamischen neuronalen Netzen". Archived 2015-03-06 at the Wayback Machine. Diploma thesis. Institut f. Informatik, Technische Univ. Munich. Advisor: J. Schmidhuber, 1991.

sferics.idsia.ch

Schmidhuber, Jürgen (1992). "Learning complex, extended sequences using the principle of history compression (based on TR FKI-148, 1991)" (PDF). Neural Computation. 4 (2): 234–242. doi:10.1162/neco.1992.4.2.234. S2CID 18271205.
Schmidhuber, Jürgen (1993). Habilitation thesis: System modeling and optimization (PDF).^{[permanent dead link‍]} Page 150 ff demonstrates credit assignment across the equivalent of 1,200 layers in an unfolded RNN.

ieee.org

ieeexplore.ieee.org

He, Kaiming; Zhang, Xiangyu; Ren, Shaoqing; Sun, Jian (2016). Deep Residual Learning for Image Recognition. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA: IEEE. pp. 770–778. arXiv:1512.03385. doi:10.1109/CVPR.2016.90. ISBN 978-1-4673-8851-1.
Oktem, Figen S.; Kar, Oğuzhan Fatih; Bezek, Can Deniz; Kamalabadi, Farzad (2021). "High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction". IEEE Transactions on Computational Imaging. 7: 489–504. arXiv:2008.11625. doi:10.1109/TCI.2021.3075349. ISSN 2333-9403. S2CID 235340737.
Bernhardt, Melanie; Vishnevskiy, Valery; Rau, Richard; Goksel, Orcun (December 2020). "Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67 (12): 2584–2594. arXiv:2006.14395. doi:10.1109/TUFFC.2020.3010186. ISSN 1525-8955. PMID 32746211. S2CID 220055785.

ijcai.org

Ciresan, D. C.; Meier, U.; Masci, J.; Gambardella, L.M.; Schmidhuber, J. (2011). "Flexible, High Performance Convolutional Neural Networks for Image Classification" (PDF). International Joint Conference on Artificial Intelligence. doi:10.5591/978-1-57735-516-8/ijcai11-210. Archived (PDF) from the original on 2014-09-29. Retrieved 2017-06-13.

imag.fr

www-clips.imag.fr

Boitet, Christian; Blanchon, Hervé; Seligman, Mark; Bellynck, Valérie (2010). "MT on and for the Web" (PDF). Archived from the original (PDF) on 29 March 2017. Retrieved 1 December 2016.

informationweek.com

"GPUs Continue to Dominate the AI Accelerator Market for Now". InformationWeek. December 2019. Archived from the original on 10 June 2020. Retrieved 11 June 2020.

inria.fr

hal.inria.fr

Chellapilla, Kumar; Puri, Sidd; Simard, Patrice (2006), High performance convolutional neural networks for document processing, archived from the original on 2020-05-18, retrieved 2021-02-14

kaggle.com

"Merck Molecular Activity Challenge". kaggle.com. Archived from the original on 2020-07-16. Retrieved 2020-07-16.

kb.se

urn.kb.se

Forslid, Gustav; Wieslander, Hakan; Bengtsson, Ewert; Wahlby, Carolina; Hirsch, Jan-Michael; Stark, Christina Runow; Sadanandan, Sajith Kecheril (2017). "Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy". 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). pp. 82–89. doi:10.1109/ICCVW.2017.18. ISBN 9781538610343. S2CID 4728736. Archived from the original on 2021-05-09. Retrieved 2019-11-12.

kit.edu

isl.anthropomatik.kit.edu

Waibel, Alex (December 1987). Phoneme Recognition Using Time-Delay Neural Networks (PDF). Meeting of the Institute of Electrical, Information and Communication Engineers (IEICE). Tokyo, Japan.

kqed.org

ww2.kqed.org

"Startup Harnesses Supercomputers to Seek Cures". KQED Future of You. 27 May 2015. Archived from the original on 24 December 2015. Retrieved 9 November 2015.

lecun.com

yann.lecun.com

LeCun, Yann; Léon Bottou; Yoshua Bengio; Patrick Haffner (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE. 86 (11): 2278–2324. CiteSeerX 10.1.1.32.9552. doi:10.1109/5.726791. S2CID 14542261. Retrieved October 7, 2016.
"MNIST handwritten digit database, Yann LeCun, Corinna Cortes and Chris Burges". yann.lecun.com. Archived from the original on 2014-01-13. Retrieved 2014-01-28.

medium.com

ramkrishna2910.medium.com

Sivakumar, Ramakrishnan (2023-11-27). "GraphCast: A breakthrough in Weather Forecasting". Medium. Retrieved 2024-05-19.

medium.com

Marcus, Gary (14 January 2018). "In defense of skepticism about deep learning". Gary Marcus. Archived from the original on 12 October 2018. Retrieved 11 October 2018.

microsoft.com

Deng, L.; Hinton, G.; Kingsbury, B. (May 2013). "New types of deep neural network learning for speech recognition and related applications: An overview (ICASSP)" (PDF). Microsoft. Archived (PDF) from the original on 2017-09-26. Retrieved 27 December 2023.
"Deng receives prestigious IEEE Technical Achievement Award - Microsoft Research". Microsoft Research. 3 December 2015. Archived from the original on 16 March 2018. Retrieved 16 March 2018.
Yu, D.; Deng, L. (2010). "Roles of Pre-Training and Fine-Tuning in Context-Dependent DBN-HMMs for Real-World Speech Recognition". NIPS Workshop on Deep Learning and Unsupervised Feature Learning. Archived from the original on 2017-10-12. Retrieved 2017-06-14.
Seide, F.; Li, G.; Yu, D. (2011). "Conversational speech transcription using context-dependent deep neural networks". Interspeech 2011. pp. 437–440. doi:10.21437/Interspeech.2011-169. S2CID 398770. Archived from the original on 2017-10-12. Retrieved 2017-06-14.
Deng, Li; Li, Jinyu; Huang, Jui-Ting; Yao, Kaisheng; Yu, Dong; Seide, Frank; Seltzer, Mike; Zweig, Geoff; He, Xiaodong (1 May 2013). "Recent Advances in Deep Learning for Speech Research at Microsoft". Microsoft Research. Archived from the original on 12 October 2017. Retrieved 14 June 2017.
Shen, Yelong; He, Xiaodong; Gao, Jianfeng; Deng, Li; Mesnil, Gregoire (1 November 2014). "A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval". Microsoft Research. Archived from the original on 27 October 2017. Retrieved 14 June 2017.
Huang, Po-Sen; He, Xiaodong; Gao, Jianfeng; Deng, Li; Acero, Alex; Heck, Larry (1 October 2013). "Learning Deep Structured Semantic Models for Web Search using Clickthrough Data". Microsoft Research. Archived from the original on 27 October 2017. Retrieved 14 June 2017.
Gao, Jianfeng; He, Xiaodong; Yih, Scott Wen-tau; Deng, Li (1 June 2014). "Learning Continuous Phrase Representations for Translation Modeling". Microsoft Research. Archived from the original on 27 October 2017. Retrieved 14 June 2017.
"Deep Learning for Natural Language Processing: Theory and Practice (CIKM2014 Tutorial) - Microsoft Research". Microsoft Research. Archived from the original on 13 March 2017. Retrieved 14 June 2017.
Elkahky, Ali Mamdouh; Song, Yang; He, Xiaodong (1 May 2015). "A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems". Microsoft Research. Archived from the original on 25 January 2018. Retrieved 14 June 2017.

research.microsoft.com

Deng, L.; Yu, D. (2014). "Deep Learning: Methods and Applications" (PDF). Foundations and Trends in Signal Processing. 7 (3–4): 1–199. doi:10.1561/2000000039. Archived (PDF) from the original on 2016-03-14. Retrieved 2014-10-18.

mit.edu

news.mit.edu

"Study urges caution when comparing neural networks to the brain". MIT News | Massachusetts Institute of Technology. 2022-11-02. Retrieved 2023-12-06.

direct.mit.edu

Hinton, Geoffrey E.; Osindero, Simon; Teh, Yee-Whye (July 2006). "A Fast Learning Algorithm for Deep Belief Nets". Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. ISSN 0899-7667. PMID 16764513.

mlr.press

proceedings.mlr.press

Sohl-Dickstein, Jascha; Weiss, Eric; Maheswaranathan, Niru; Ganguli, Surya (2015-06-01). "Deep Unsupervised Learning using Nonequilibrium Thermodynamics" (PDF). Proceedings of the 32nd International Conference on Machine Learning. 37. PMLR: 2256–2265. arXiv:1503.03585.

nature.com

Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (October 1986). "Learning representations by back-propagating errors". Nature. 323 (6088): 533–536. Bibcode:1986Natur.323..533R. doi:10.1038/323533a0. ISSN 1476-4687.
Peplow, Mark (2023-11-29). "Google AI and robots join forces to build new materials". Nature. doi:10.1038/d41586-023-03745-5. PMID 38030771. S2CID 265503872.
Gibney, Elizabeth (2017). "The scientist who spots fake videos". Nature. doi:10.1038/nature.2017.22784. Archived from the original on 2017-10-10. Retrieved 2017-10-11.

newyorker.com

Marcus, Gary (November 25, 2012). "Is "Deep Learning" a Revolution in Artificial Intelligence?". The New Yorker. Archived from the original on 2009-11-27. Retrieved 2017-06-14.

nih.gov

pubmed.ncbi.nlm.nih.gov

LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep Learning" (PDF). Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442. S2CID 3074096.
Bengio, Y.; Courville, A.; Vincent, P. (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. doi:10.1109/tpami.2013.50. PMID 23787338. S2CID 393948.
Schmidhuber, J. (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Orhan, A. E.; Ma, W. J. (2017). "Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback". Nature Communications. 8 (1): 138. Bibcode:2017NatCo...8..138O. doi:10.1038/s41467-017-00181-8. PMC 5527101. PMID 28743932.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554. PMC 346238. PMID 6953413.
Rosenblatt, F. (1958). "The perceptron: A probabilistic model for information storage and organization in the brain". Psychological Review. 65 (6): 386–408. doi:10.1037/h0042519. ISSN 1939-1471. PMID 13602029.
Fukushima, K. (1979). "Neural network model for a mechanism of pattern recognition unaffected by shift in position—Neocognitron". Trans. IECE (In Japanese). J62-A (10): 658–665. doi:10.1007/bf00344251. PMID 7370364. S2CID 206775608.
Fukushima, K. (1980). "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position". Biol. Cybern. 36 (4): 193–202. doi:10.1007/bf00344251. PMID 7370364. S2CID 206775608.
Zhang, Wei (1990). "Parallel distributed processing model with local space-invariant interconnections and its optical architecture". Applied Optics. 29 (32): 4790–7. Bibcode:1990ApOpt..29.4790Z. doi:10.1364/AO.29.004790. PMID 20577468.
Zhang, Wei (1991). "Image processing of human corneal endothelium based on a learning network". Applied Optics. 30 (29): 4211–7. Bibcode:1991ApOpt..30.4211Z. doi:10.1364/AO.30.004211. PMID 20706526.
Zhang, Wei (1994). "Computerized detection of clustered microcalcifications in digital mammograms using a shift-invariant artificial neural network". Medical Physics. 21 (4): 517–24. Bibcode:1994MedPh..21..517Z. doi:10.1118/1.597177. PMID 8058017.
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks. 127: 58–66. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008. PMID 32334341. S2CID 216056336.
Peter, Dayan; Hinton, Geoffrey E.; Neal, Radford M.; Zemel, Richard S. (1995). "The Helmholtz machine". Neural Computation. 7 (5): 889–904. doi:10.1162/neco.1995.7.5.889. hdl:21.11116/0000-0002-D6D3-E. PMID 7584891. S2CID 1890561.
Hinton, Geoffrey E.; Dayan, Peter; Frey, Brendan J.; Neal, Radford (1995-05-26). "The wake-sleep algorithm for unsupervised neural networks". Science. 268 (5214): 1158–1161. Bibcode:1995Sci...268.1158H. doi:10.1126/science.7761831. PMID 7761831. S2CID 871473.
Qian, Ning; Sejnowski, Terrence J. (1988-08-20). "Predicting the secondary structure of globular proteins using neural network models". Journal of Molecular Biology. 202 (4): 865–884. doi:10.1016/0022-2836(88)90564-5. ISSN 0022-2836. PMID 3172241.
Hinton, Geoffrey E. (1 October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. ISSN 1364-6613. PMID 17921042. S2CID 15066318. Archived from the original on 11 October 2013. Retrieved 12 June 2017.
Hinton, G. E.; Osindero, S.; Teh, Y. W. (2006). "A Fast Learning Algorithm for Deep Belief Nets" (PDF). Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950. Archived (PDF) from the original on 2015-12-23. Retrieved 2011-07-20.
Hinton, Geoffrey E. (October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. PMID 17921042.
Hinton, Geoffrey E.; Osindero, Simon; Teh, Yee-Whye (July 2006). "A Fast Learning Algorithm for Deep Belief Nets". Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. ISSN 0899-7667. PMID 16764513.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (21 September 2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation. 22 (12): 3207–3220. arXiv:1003.0358. doi:10.1162/neco_a_00052. ISSN 0899-7667. PMID 20858131. S2CID 1918673.
Ciresan, D.; Giusti, A.; Gambardella, L.M.; Schmidhuber, J. (2013). "Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks". Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. Lecture Notes in Computer Science. Vol. 7908. pp. 411–418. doi:10.1007/978-3-642-40763-5_51. ISBN 978-3-642-38708-1. PMID 24579167.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042. S2CID 515925.
Gers, Felix A.; Schmidhuber, Jürgen (2001). "LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages". IEEE Transactions on Neural Networks. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962. S2CID 10192330. Archived from the original on 2020-01-26. Retrieved 2020-02-25.
Hochreiter, Sepp; Schmidhuber, Jürgen (1 November 1997). "Long Short-Term Memory". Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276. S2CID 1915014.
Marega, Guilherme Migliato; Zhao, Yanfei; Avsar, Ahmet; Wang, Zhenyu; Tripati, Mukesh; Radenovic, Aleksandra; Kis, Anras (2020). "Logic-in-memory based on an atomically thin semiconductor". Nature. 587 (2): 72–77. Bibcode:2020Natur.587...72M. doi:10.1038/s41586-020-2861-0. PMC 7116757. PMID 33149289.
Feldmann, J.; Youngblood, N.; Karpov, M.; et al. (2021). "Parallel convolutional processing using an integrated photonic tensor". Nature. 589 (2): 52–58. arXiv:2002.00281. doi:10.1038/s41586-020-03070-1. PMID 33408373. S2CID 211010976.
Cireşan, Dan; Meier, Ueli; Masci, Jonathan; Schmidhuber, Jürgen (August 2012). "Multi-column deep neural network for traffic sign classification". Neural Networks. Selected Papers from IJCNN 2011. 32: 333–338. CiteSeerX 10.1.1.226.8219. doi:10.1016/j.neunet.2012.02.023. PMID 22386783.
Kariampuzha, William; Alyea, Gioconda; Qu, Sue; Sanjak, Jaleal; Mathé, Ewy; Sid, Eric; Chatelaine, Haley; Yadaw, Arjun; Xu, Yanji; Zhu, Qian (2023). "Precision information extraction for rare disease epidemiology at scale". Journal of Translational Medicine. 21 (1): 157. doi:10.1186/s12967-023-04011-y. PMC 9972634. PMID 36855134.
Arrowsmith, J; Miller, P (2013). "Trial watch: Phase II and phase III attrition rates 2011-2012". Nature Reviews Drug Discovery. 12 (8): 569. doi:10.1038/nrd4090. PMID 23903212. S2CID 20246434.
Verbist, B; Klambauer, G; Vervoort, L; Talloen, W; The Qstar, Consortium; Shkedy, Z; Thas, O; Bender, A; Göhlmann, H. W.; Hochreiter, S (2015). "Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project". Drug Discovery Today. 20 (5): 505–513. doi:10.1016/j.drudis.2014.12.014. hdl:1942/18723. PMID 25582842.
Zhavoronkov, Alex (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors". Nature Biotechnology. 37 (9): 1038–1040. doi:10.1038/s41587-019-0224-x. PMID 31477924. S2CID 201716327.
Feng, X.Y.; Zhang, H.; Ren, Y.J.; Shang, P.H.; Zhu, Y.; Liang, Y.C.; Guan, R.C.; Xu, D. (2019). "The Deep Learning–Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study". Journal of Medical Internet Research. 21 (5): e12957. doi:10.2196/12957. PMC 6555124. PMID 31127715.
Sathyanarayana, Aarti (1 January 2016). "Sleep Quality Prediction From Wearable Data Using Deep Learning". JMIR mHealth and uHealth. 4 (4): e125. doi:10.2196/mhealth.6562. PMC 5116102. PMID 27815231. S2CID 3821594.
Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (13 August 2016). "Using recurrent neural network models for early detection of heart failure onset". Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725. PMID 27521897.
Shalev, Y.; Painsky, A.; Ben-Gal, I. (2022). "Neural Joint Entropy Estimation" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (4): 5488–5500. arXiv:2012.11197. doi:10.1109/TNNLS.2022.3204919. PMID 36155469. S2CID 229339809.
Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (December 2017). "A survey on deep learning in medical image analysis". Medical Image Analysis. 42: 60–88. arXiv:1702.05747. Bibcode:2017arXiv170205747L. doi:10.1016/j.media.2017.07.005. PMID 28778026. S2CID 2088679.
Lyakhov, Pavel Alekseevich; Lyakhova, Ulyana Alekseevna; Nagornov, Nikolay Nikolaevich (2022-04-03). "System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of Heterogeneous Data Based on a Multimodal Neural Network". Cancers. 14 (7): 1819. doi:10.3390/cancers14071819. ISSN 2072-6694. PMC 8997449. PMID 35406591.
Merchant, Amil; Batzner, Simon; Schoenholz, Samuel S.; Aykol, Muratahan; Cheon, Gowoon; Cubuk, Ekin Dogus (December 2023). "Scaling deep learning for materials discovery". Nature. 624 (7990): 80–85. Bibcode:2023Natur.624...80M. doi:10.1038/s41586-023-06735-9. ISSN 1476-4687. PMC 10700131. PMID 38030720.
Peplow, Mark (2023-11-29). "Google AI and robots join forces to build new materials". Nature. doi:10.1038/d41586-023-03745-5. PMID 38030771. S2CID 265503872.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Han, J.; Jentzen, A.; E, W. (2018). "Solving high-dimensional partial differential equations using deep learning". Proceedings of the National Academy of Sciences. 115 (34): 8505–8510. arXiv:1707.02568. Bibcode:2018PNAS..115.8505H. doi:10.1073/pnas.1718942115. PMC 6112690. PMID 30082389.
Bernhardt, Melanie; Vishnevskiy, Valery; Rau, Richard; Goksel, Orcun (December 2020). "Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67 (12): 2584–2594. arXiv:2006.14395. doi:10.1109/TUFFC.2020.3010186. ISSN 1525-8955. PMID 32746211. S2CID 220055785.
Lam, Remi; Sanchez-Gonzalez, Alvaro; Willson, Matthew; Wirnsberger, Peter; Fortunato, Meire; Alet, Ferran; Ravuri, Suman; Ewalds, Timo; Eaton-Rosen, Zach; Hu, Weihua; Merose, Alexander; Hoyer, Stephan; Holland, George; Vinyals, Oriol; Stott, Jacklynn (2023-12-22). "Learning skillful medium-range global weather forecasting". Science. 382 (6677): 1416–1421. arXiv:2212.12794. Bibcode:2023Sci...382.1416L. doi:10.1126/science.adi2336. ISSN 0036-8075. PMID 37962497.
Utgoff, P. E.; Stracuzzi, D. J. (2002). "Many-layered learning". Neural Computation. 14 (10): 2497–2529. doi:10.1162/08997660260293319. PMID 12396572. S2CID 1119517.
Shrager, J.; Johnson, MH (1996). "Dynamic plasticity influences the emergence of function in a simple cortical array". Neural Networks. 9 (7): 1119–1129. doi:10.1016/0893-6080(96)00033-0. PMID 12662587.
Quartz, SR; Sejnowski, TJ (1997). "The neural basis of cognitive development: A constructivist manifesto". Behavioral and Brain Sciences. 20 (4): 537–556. CiteSeerX 10.1.1.41.7854. doi:10.1017/s0140525x97001581. PMID 10097006. S2CID 5818342.
Mazzoni, P.; Andersen, R. A.; Jordan, M. I. (15 May 1991). "A more biologically plausible learning rule for neural networks". Proceedings of the National Academy of Sciences. 88 (10): 4433–4437. Bibcode:1991PNAS...88.4433M. doi:10.1073/pnas.88.10.4433. ISSN 0027-8424. PMC 51674. PMID 1903542.
Testolin, Alberto; Zorzi, Marco (2016). "Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions". Frontiers in Computational Neuroscience. 10: 73. doi:10.3389/fncom.2016.00073. ISSN 1662-5188. PMC 4943066. PMID 27468262. S2CID 9868901.
Testolin, Alberto; Stoianov, Ivilin; Zorzi, Marco (September 2017). "Letter perception emerges from unsupervised deep learning and recycling of natural image features". Nature Human Behaviour. 1 (9): 657–664. doi:10.1038/s41562-017-0186-2. ISSN 2397-3374. PMID 31024135. S2CID 24504018.
Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS Computational Biology. 7 (11): e1002211. Bibcode:2011PLSCB...7E2211B. doi:10.1371/journal.pcbi.1002211. ISSN 1553-7358. PMC 3207943. PMID 22096452. S2CID 7504633.
Cash, S.; Yuste, R. (February 1999). "Linear summation of excitatory inputs by CA1 pyramidal neurons". Neuron. 22 (2): 383–394. doi:10.1016/s0896-6273(00)81098-3. ISSN 0896-6273. PMID 10069343. S2CID 14663106.
Olshausen, B; Field, D (1 August 2004). "Sparse coding of sensory inputs". Current Opinion in Neurobiology. 14 (4): 481–487. doi:10.1016/j.conb.2004.07.007. ISSN 0959-4388. PMID 15321069. S2CID 16560320.
Yamins, Daniel L K; DiCarlo, James J (March 2016). "Using goal-driven deep learning models to understand sensory cortex". Nature Neuroscience. 19 (3): 356–365. doi:10.1038/nn.4244. ISSN 1546-1726. PMID 26906502. S2CID 16970545.
Zorzi, Marco; Testolin, Alberto (19 February 2018). "An emergentist perspective on the origin of number sense". Phil. Trans. R. Soc. B. 373 (1740): 20170043. doi:10.1098/rstb.2017.0043. ISSN 0962-8436. PMC 5784047. PMID 29292348. S2CID 39281431.
Güçlü, Umut; van Gerven, Marcel A. J. (8 July 2015). "Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream". Journal of Neuroscience. 35 (27): 10005–10014. arXiv:1411.6422. doi:10.1523/jneurosci.5023-14.2015. PMC 6605414. PMID 26157000.
Gibney, Elizabeth (2016). "Google AI algorithm masters ancient game of Go". Nature. 529 (7587): 445–446. Bibcode:2016Natur.529..445G. doi:10.1038/529445a. PMID 26819021. S2CID 4460235.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.

ncbi.nlm.nih.gov

Orhan, A. E.; Ma, W. J. (2017). "Efficient probabilistic inference in generic neural networks trained with non-probabilistic feedback". Nature Communications. 8 (1): 138. Bibcode:2017NatCo...8..138O. doi:10.1038/s41467-017-00181-8. PMC 5527101. PMID 28743932.
Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. Bibcode:1982PNAS...79.2554H. doi:10.1073/pnas.79.8.2554. PMC 346238. PMID 6953413.
Marega, Guilherme Migliato; Zhao, Yanfei; Avsar, Ahmet; Wang, Zhenyu; Tripati, Mukesh; Radenovic, Aleksandra; Kis, Anras (2020). "Logic-in-memory based on an atomically thin semiconductor". Nature. 587 (2): 72–77. Bibcode:2020Natur.587...72M. doi:10.1038/s41586-020-2861-0. PMC 7116757. PMID 33149289.
Kariampuzha, William; Alyea, Gioconda; Qu, Sue; Sanjak, Jaleal; Mathé, Ewy; Sid, Eric; Chatelaine, Haley; Yadaw, Arjun; Xu, Yanji; Zhu, Qian (2023). "Precision information extraction for rare disease epidemiology at scale". Journal of Translational Medicine. 21 (1): 157. doi:10.1186/s12967-023-04011-y. PMC 9972634. PMID 36855134.
Feng, X.Y.; Zhang, H.; Ren, Y.J.; Shang, P.H.; Zhu, Y.; Liang, Y.C.; Guan, R.C.; Xu, D. (2019). "The Deep Learning–Based Recommender System "Pubmender" for Choosing a Biomedical Publication Venue: Development and Validation Study". Journal of Medical Internet Research. 21 (5): e12957. doi:10.2196/12957. PMC 6555124. PMID 31127715.
Sathyanarayana, Aarti (1 January 2016). "Sleep Quality Prediction From Wearable Data Using Deep Learning". JMIR mHealth and uHealth. 4 (4): e125. doi:10.2196/mhealth.6562. PMC 5116102. PMID 27815231. S2CID 3821594.
Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (13 August 2016). "Using recurrent neural network models for early detection of heart failure onset". Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725. PMID 27521897.
Lyakhov, Pavel Alekseevich; Lyakhova, Ulyana Alekseevna; Nagornov, Nikolay Nikolaevich (2022-04-03). "System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of Heterogeneous Data Based on a Multimodal Neural Network". Cancers. 14 (7): 1819. doi:10.3390/cancers14071819. ISSN 2072-6694. PMC 8997449. PMID 35406591.
Merchant, Amil; Batzner, Simon; Schoenholz, Samuel S.; Aykol, Muratahan; Cheon, Gowoon; Cubuk, Ekin Dogus (December 2023). "Scaling deep learning for materials discovery". Nature. 624 (7990): 80–85. Bibcode:2023Natur.624...80M. doi:10.1038/s41586-023-06735-9. ISSN 1476-4687. PMC 10700131. PMID 38030720.
Raissi, Maziar; Yazdani, Alireza; Karniadakis, George Em (2020-02-28). "Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations". Science. 367 (6481): 1026–1030. Bibcode:2020Sci...367.1026R. doi:10.1126/science.aaw4741. PMC 7219083. PMID 32001523.
Han, J.; Jentzen, A.; E, W. (2018). "Solving high-dimensional partial differential equations using deep learning". Proceedings of the National Academy of Sciences. 115 (34): 8505–8510. arXiv:1707.02568. Bibcode:2018PNAS..115.8505H. doi:10.1073/pnas.1718942115. PMC 6112690. PMID 30082389.
Mazzoni, P.; Andersen, R. A.; Jordan, M. I. (15 May 1991). "A more biologically plausible learning rule for neural networks". Proceedings of the National Academy of Sciences. 88 (10): 4433–4437. Bibcode:1991PNAS...88.4433M. doi:10.1073/pnas.88.10.4433. ISSN 0027-8424. PMC 51674. PMID 1903542.
Testolin, Alberto; Zorzi, Marco (2016). "Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions". Frontiers in Computational Neuroscience. 10: 73. doi:10.3389/fncom.2016.00073. ISSN 1662-5188. PMC 4943066. PMID 27468262. S2CID 9868901.
Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS Computational Biology. 7 (11): e1002211. Bibcode:2011PLSCB...7E2211B. doi:10.1371/journal.pcbi.1002211. ISSN 1553-7358. PMC 3207943. PMID 22096452. S2CID 7504633.
Zorzi, Marco; Testolin, Alberto (19 February 2018). "An emergentist perspective on the origin of number sense". Phil. Trans. R. Soc. B. 373 (1740): 20170043. doi:10.1098/rstb.2017.0043. ISSN 0962-8436. PMC 5784047. PMID 29292348. S2CID 39281431.
Güçlü, Umut; van Gerven, Marcel A. J. (8 July 2015). "Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream". Journal of Neuroscience. 35 (27): 10005–10014. arXiv:1411.6422. doi:10.1523/jneurosci.5023-14.2015. PMC 6605414. PMID 26157000.

tripod.nih.gov

"NCATS Announces Tox21 Data Challenge Winners". Archived from the original on 2015-09-08. Retrieved 2015-03-05.

ncats.nih.gov

"NCATS Announces Tox21 Data Challenge Winners". Archived from the original on 28 February 2015. Retrieved 5 March 2015.

nips.cc

papers.nips.cc

Bengio, Yoshua; Lamblin, Pascal; Popovici, Dan; Larochelle, Hugo (2007). Greedy layer-wise training of deep networks (PDF). Advances in neural information processing systems. pp. 153–160. Archived (PDF) from the original on 2019-10-20. Retrieved 2019-10-06.
Lu, Z., Pu, H., Wang, F., Hu, Z., & Wang, L. (2017). The Expressive Power of Neural Networks: A View from the Width Archived 2019-02-13 at the Wayback Machine. Neural Information Processing Systems, 6231-6239.
Ciresan, Dan; Giusti, Alessandro; Gambardella, Luca M.; Schmidhuber, Jürgen (2012). Pereira, F.; Burges, C. J. C.; Bottou, L.; Weinberger, K. Q. (eds.). Advances in Neural Information Processing Systems 25 (PDF). Curran Associates, Inc. pp. 2843–2851. Archived (PDF) from the original on 2017-08-09. Retrieved 2017-06-13.
Goodfellow, Ian; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). Generative Adversarial Networks (PDF). Proceedings of the International Conference on Neural Information Processing Systems (NIPS 2014). pp. 2672–2680. Archived (PDF) from the original on 22 November 2019. Retrieved 20 August 2019.
Szegedy, Christian; Toshev, Alexander; Erhan, Dumitru (2013). "Deep neural networks for object detection". Advances in Neural Information Processing Systems: 2553–2561. Archived from the original on 2017-06-29. Retrieved 2017-06-13.
Sutskever, L.; Vinyals, O.; Le, Q. (2014). "Sequence to Sequence Learning with Neural Networks" (PDF). Proc. NIPS. arXiv:1409.3215. Bibcode:2014arXiv1409.3215S. Archived (PDF) from the original on 2021-05-09. Retrieved 2017-06-13.
van den Oord, Aaron; Dieleman, Sander; Schrauwen, Benjamin (2013). Burges, C. J. C.; Bottou, L.; Welling, M.; Ghahramani, Z.; Weinberger, K. Q. (eds.). Advances in Neural Information Processing Systems 26 (PDF). Curran Associates, Inc. pp. 2643–2651. Archived (PDF) from the original on 2017-05-16. Retrieved 2017-06-14.

nytimes.com

Metz, Cade (6 November 2017). "A.I. Researchers Leave Elon Musk Lab to Begin Robotics Start-Up". The New York Times. Archived from the original on 7 July 2019. Retrieved 5 July 2019.

openai.com

"AI and Compute". OpenAI. 16 May 2018. Archived from the original on 17 June 2020. Retrieved 11 June 2020.

openreview.net

Rolnick, David; Tegmark, Max (2018). "The power of deeper networks for expressing natural functions". International Conference on Learning Representations. ICLR 2018. Archived from the original on 2021-01-07. Retrieved 2021-01-05.

osti.gov

Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.

psu.edu

citeseerx.ist.psu.edu

Bengio, Yoshua (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. S2CID 207178999. Archived from the original (PDF) on 4 March 2016. Retrieved 3 September 2015.
LeCun, Yann; Léon Bottou; Yoshua Bengio; Patrick Haffner (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE. 86 (11): 2278–2324. CiteSeerX 10.1.1.32.9552. doi:10.1109/5.726791. S2CID 14542261. Retrieved October 7, 2016.
Graves, Alex; Fernández, Santiago; Gomez, Faustino; Schmidhuber, Jürgen (2006). "Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks". Proceedings of the International Conference on Machine Learning, ICML 2006: 369–376. CiteSeerX 10.1.1.75.6306.
Bengio, Yoshua; Boulanger-Lewandowski, Nicolas; Pascanu, Razvan (2013). "Advances in optimizing recurrent networks". 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 8624–8628. arXiv:1212.0901. CiteSeerX 10.1.1.752.9151. doi:10.1109/icassp.2013.6639349. ISBN 978-1-4799-0356-6. S2CID 12485056.
Cireşan, Dan; Meier, Ueli; Masci, Jonathan; Schmidhuber, Jürgen (August 2012). "Multi-column deep neural network for traffic sign classification". Neural Networks. Selected Papers from IJCNN 2011. 32: 333–338. CiteSeerX 10.1.1.226.8219. doi:10.1016/j.neunet.2012.02.023. PMID 22386783.
Quartz, SR; Sejnowski, TJ (1997). "The neural basis of cognitive development: A constructivist manifesto". Behavioral and Brain Sciences. 20 (4): 537–556. CiteSeerX 10.1.1.41.7854. doi:10.1017/s0140525x97001581. PMID 10097006. S2CID 5818342.
Zhu, S.C.; Mumford, D. (2006). "A stochastic grammar of images". Found. Trends Comput. Graph. Vis. 2 (4): 259–362. CiteSeerX 10.1.1.681.2190. doi:10.1561/0600000018.

researchgate.net

Rina Dechter (1986). Learning while searching in constraint-satisfaction problems. University of California, Computer Science Department, Cognitive Systems Laboratory.Online Archived 2016-04-19 at the Wayback Machine
Bengio, Y. (1991). "Artificial Neural Networks and their Application to Speech/Sequence Recognition". McGill University Ph.D. thesis. Archived from the original on 2021-05-09. Retrieved 2017-06-12.
"Acoustic Modeling with Deep Neural Networks Using Raw Time Signal for LVCSR (PDF Download Available)". ResearchGate. Archived from the original on 9 May 2021. Retrieved 14 June 2017.
"Learning Precise Timing with LSTM Recurrent Networks (PDF Download Available)". ResearchGate. Archived from the original on 9 May 2021. Retrieved 13 June 2017.
Hinton, G. E. (2010). "A Practical Guide to Training Restricted Boltzmann Machines". Tech. Rep. UTML TR 2010-003. Archived from the original on 2021-05-09. Retrieved 2017-06-13.

sanghv.com

Bengio, Yoshua (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. S2CID 207178999. Archived from the original (PDF) on 4 March 2016. Retrieved 3 September 2015.

sciencedirect.com

Ackley, David H.; Hinton, Geoffrey E.; Sejnowski, Terrence J. (1985-01-01). "A learning algorithm for boltzmann machines". Cognitive Science. 9 (1): 147–169. doi:10.1016/S0364-0213(85)80012-4. ISSN 0364-0213.

semanticscholar.org

api.semanticscholar.org

Schulz, Hannes; Behnke, Sven (1 November 2012). "Deep Learning". KI - Künstliche Intelligenz. 26 (4): 357–363. doi:10.1007/s13218-012-0198-z. ISSN 1610-1987. S2CID 220523562.
LeCun, Yann; Bengio, Yoshua; Hinton, Geoffrey (2015). "Deep Learning" (PDF). Nature. 521 (7553): 436–444. Bibcode:2015Natur.521..436L. doi:10.1038/nature14539. PMID 26017442. S2CID 3074096.
Ciresan, D.; Meier, U.; Schmidhuber, J. (2012). "Multi-column deep neural networks for image classification". 2012 IEEE Conference on Computer Vision and Pattern Recognition. pp. 3642–3649. arXiv:1202.2745. doi:10.1109/cvpr.2012.6248110. ISBN 978-1-4673-1228-8. S2CID 2161592.
Bengio, Yoshua (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. S2CID 207178999. Archived from the original (PDF) on 4 March 2016. Retrieved 3 September 2015.
Bengio, Y.; Courville, A.; Vincent, P. (2013). "Representation Learning: A Review and New Perspectives". IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (8): 1798–1828. arXiv:1206.5538. doi:10.1109/tpami.2013.50. PMID 23787338. S2CID 393948.
Schmidhuber, J. (2015). "Deep Learning in Neural Networks: An Overview". Neural Networks. 61: 85–117. arXiv:1404.7828. doi:10.1016/j.neunet.2014.09.003. PMID 25462637. S2CID 11715509.
Fradkov, Alexander L. (2020-01-01). "Early History of Machine Learning". IFAC-PapersOnLine. 21st IFAC World Congress. 53 (2): 1385–1390. doi:10.1016/j.ifacol.2020.12.1888. ISSN 2405-8963. S2CID 235081987.
Cybenko (1989). "Approximations by superpositions of sigmoidal functions" (PDF). Mathematics of Control, Signals, and Systems. 2 (4): 303–314. Bibcode:1989MCSS....2..303C. doi:10.1007/bf02551274. S2CID 3958369. Archived from the original (PDF) on 10 October 2015.
Hornik, Kurt (1991). "Approximation Capabilities of Multilayer Feedforward Networks". Neural Networks. 4 (2): 251–257. doi:10.1016/0893-6080(91)90009-t. S2CID 7343126.
Sonoda, Sho; Murata, Noboru (2017). "Neural network with unbounded activation functions is universal approximator". Applied and Computational Harmonic Analysis. 43 (2): 233–268. arXiv:1505.03654. doi:10.1016/j.acha.2015.12.005. S2CID 12149203.
Fukushima, K. (1979). "Neural network model for a mechanism of pattern recognition unaffected by shift in position—Neocognitron". Trans. IECE (In Japanese). J62-A (10): 658–665. doi:10.1007/bf00344251. PMID 7370364. S2CID 206775608.
Fukushima, K. (1980). "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position". Biol. Cybern. 36 (4): 193–202. doi:10.1007/bf00344251. PMID 7370364. S2CID 206775608.
Linnainmaa, Seppo (1976). "Taylor expansion of the accumulated rounding error". BIT Numerical Mathematics. 16 (2): 146–160. doi:10.1007/bf01931367. S2CID 122357351.
LeCun, Yann; Léon Bottou; Yoshua Bengio; Patrick Haffner (1998). "Gradient-based learning applied to document recognition" (PDF). Proceedings of the IEEE. 86 (11): 2278–2324. CiteSeerX 10.1.1.32.9552. doi:10.1109/5.726791. S2CID 14542261. Retrieved October 7, 2016.
Schmidhuber, Jürgen (1992). "Learning complex, extended sequences using the principle of history compression (based on TR FKI-148, 1991)" (PDF). Neural Computation. 4 (2): 234–242. doi:10.1162/neco.1992.4.2.234. S2CID 18271205.
Schmidhuber, Jürgen (2010). "Formal Theory of Creativity, Fun, and Intrinsic Motivation (1990-2010)". IEEE Transactions on Autonomous Mental Development. 2 (3): 230–247. doi:10.1109/TAMD.2010.2056368. S2CID 234198.
Schmidhuber, Jürgen (2020). "Generative Adversarial Networks are Special Cases of Artificial Curiosity (1990) and also Closely Related to Predictability Minimization (1991)". Neural Networks. 127: 58–66. arXiv:1906.04493. doi:10.1016/j.neunet.2020.04.008. PMID 32334341. S2CID 216056336.
Peter, Dayan; Hinton, Geoffrey E.; Neal, Radford M.; Zemel, Richard S. (1995). "The Helmholtz machine". Neural Computation. 7 (5): 889–904. doi:10.1162/neco.1995.7.5.889. hdl:21.11116/0000-0002-D6D3-E. PMID 7584891. S2CID 1890561.
Hinton, Geoffrey E.; Dayan, Peter; Frey, Brendan J.; Neal, Radford (1995-05-26). "The wake-sleep algorithm for unsupervised neural networks". Science. 268 (5214): 1158–1161. Bibcode:1995Sci...268.1158H. doi:10.1126/science.7761831. PMID 7761831. S2CID 871473.
Waibel, A.; Hanazawa, T.; Hinton, G.; Shikano, K.; Lang, K. J. (March 1989). "Phoneme recognition using time-delay neural networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 37 (3): 328–339. doi:10.1109/29.21701. hdl:10338.dmlcz/135496. ISSN 0096-3518. S2CID 9563026. Archived (PDF) from the original on 2021-04-27. Retrieved 2019-09-24.
Baker, J.; Deng, Li; Glass, Jim; Khudanpur, S.; Lee, C.-H.; Morgan, N.; O'Shaughnessy, D. (2009). "Research Developments and Directions in Speech Recognition and Understanding, Part 1". IEEE Signal Processing Magazine. 26 (3): 75–80. Bibcode:2009ISPM...26...75B. doi:10.1109/msp.2009.932166. hdl:1721.1/51891. S2CID 357467.
Hinton, Geoffrey E. (1 October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. ISSN 1364-6613. PMID 17921042. S2CID 15066318. Archived from the original on 11 October 2013. Retrieved 12 June 2017.
Hinton, G. E.; Osindero, S.; Teh, Y. W. (2006). "A Fast Learning Algorithm for Deep Belief Nets" (PDF). Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950. Archived (PDF) from the original on 2015-12-23. Retrieved 2011-07-20.
Hinton, G.; Deng, L.; Yu, D.; Dahl, G.; Mohamed, A.; Jaitly, N.; Senior, A.; Vanhoucke, V.; Nguyen, P.; Sainath, T.; Kingsbury, B. (2012). "Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups". IEEE Signal Processing Magazine. 29 (6): 82–97. Bibcode:2012ISPM...29...82H. doi:10.1109/msp.2012.2205597. S2CID 206485943.
Seide, F.; Li, G.; Yu, D. (2011). "Conversational speech transcription using context-dependent deep neural networks". Interspeech 2011. pp. 437–440. doi:10.21437/Interspeech.2011-169. S2CID 398770. Archived from the original on 2017-10-12. Retrieved 2017-06-14.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (21 September 2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation. 22 (12): 3207–3220. arXiv:1003.0358. doi:10.1162/neco_a_00052. ISSN 0899-7667. PMID 20858131. S2CID 1918673.
Singh, Premjeet; Saha, Goutam; Sahidullah, Md (2021). "Non-linear frequency warping using constant-Q transformation for speech emotion recognition". 2021 International Conference on Computer Communication and Informatics (ICCCI). pp. 1–4. arXiv:2102.04029. doi:10.1109/ICCCI50826.2021.9402569. ISBN 978-1-7281-5875-4. S2CID 231846518.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042. S2CID 515925.
Kumar, Nishant; Raubal, Martin (2021). "Applications of deep learning in congestion detection, prediction and alleviation: A survey". Transportation Research Part C: Emerging Technologies. 133: 103432. arXiv:2102.09759. Bibcode:2021TRPC..13303432K. doi:10.1016/j.trc.2021.103432. hdl:10230/42143. S2CID 240420107.
Gers, Felix A.; Schmidhuber, Jürgen (2001). "LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages". IEEE Transactions on Neural Networks. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962. S2CID 10192330. Archived from the original on 2020-01-26. Retrieved 2020-02-25.
Mikolov, T.; et al. (2010). "Recurrent neural network based language model" (PDF). Interspeech: 1045–1048. doi:10.21437/Interspeech.2010-343. S2CID 17048224. Archived (PDF) from the original on 2017-05-16. Retrieved 2017-06-13.
Hochreiter, Sepp; Schmidhuber, Jürgen (1 November 1997). "Long Short-Term Memory". Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276. S2CID 1915014.
LeCun, Y.; et al. (1998). "Gradient-based learning applied to document recognition". Proceedings of the IEEE. 86 (11): 2278–2324. doi:10.1109/5.726791. S2CID 14542261.
Sainath, Tara N.; Mohamed, Abdel-Rahman; Kingsbury, Brian; Ramabhadran, Bhuvana (2013). "Deep convolutional neural networks for LVCSR". 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 8614–8618. doi:10.1109/icassp.2013.6639347. ISBN 978-1-4799-0356-6. S2CID 13816461.
Bengio, Yoshua; Boulanger-Lewandowski, Nicolas; Pascanu, Razvan (2013). "Advances in optimizing recurrent networks". 2013 IEEE International Conference on Acoustics, Speech and Signal Processing. pp. 8624–8628. arXiv:1212.0901. CiteSeerX 10.1.1.752.9151. doi:10.1109/icassp.2013.6639349. ISBN 978-1-4799-0356-6. S2CID 12485056.
You, Yang; Buluç, Aydın; Demmel, James (November 2017). "Scaling deep learning on GPU and knights landing clusters". Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17. SC '17, ACM. pp. 1–12. doi:10.1145/3126908.3126912. ISBN 9781450351140. S2CID 8869270. Archived from the original on 29 July 2020. Retrieved 5 March 2018.
Viebke, André; Memeti, Suejb; Pllana, Sabri; Abraham, Ajith (2019). "CHAOS: a parallelization scheme for training convolutional neural networks on Intel Xeon Phi". The Journal of Supercomputing. 75: 197–227. arXiv:1702.07908. Bibcode:2017arXiv170207908V. doi:10.1007/s11227-017-1994-x. S2CID 14135321.
Feldmann, J.; Youngblood, N.; Karpov, M.; et al. (2021). "Parallel convolutional processing using an integrated photonic tensor". Nature. 589 (2): 52–58. arXiv:2002.00281. doi:10.1038/s41586-020-03070-1. PMID 33408373. S2CID 211010976.
Abdel-Hamid, O.; et al. (2014). "Convolutional Neural Networks for Speech Recognition". IEEE/ACM Transactions on Audio, Speech, and Language Processing. 22 (10): 1533–1545. doi:10.1109/taslp.2014.2339736. S2CID 206602362. Archived from the original on 2020-09-22. Retrieved 2018-04-20.
Deng, L.; Platt, J. (2014). "Ensemble Deep Learning for Speech Recognition". Proc. Interspeech: 1915–1919. doi:10.21437/Interspeech.2014-433. S2CID 15641618.
Tóth, Laszló (2015). "Phone Recognition with Hierarchical Convolutional Deep Maxout Networks" (PDF). EURASIP Journal on Audio, Speech, and Music Processing. 2015. doi:10.1186/s13636-015-0068-3. S2CID 217950236. Archived (PDF) from the original on 2020-09-24. Retrieved 2019-04-01.
Mesnil, G.; Dauphin, Y.; Yao, K.; Bengio, Y.; Deng, L.; Hakkani-Tur, D.; He, X.; Heck, L.; Tur, G.; Yu, D.; Zweig, G. (2015). "Using recurrent neural networks for slot filling in spoken language understanding". IEEE Transactions on Audio, Speech, and Language Processing. 23 (3): 530–539. doi:10.1109/taslp.2014.2383614. S2CID 1317136.
Brocardo, Marcelo Luiz; Traore, Issa; Woungang, Isaac; Obaidat, Mohammad S. (2017). "Authorship verification using deep belief network systems". International Journal of Communication Systems. 30 (12): e3259. doi:10.1002/dac.3259. S2CID 40745740.
Arrowsmith, J; Miller, P (2013). "Trial watch: Phase II and phase III attrition rates 2011-2012". Nature Reviews Drug Discovery. 12 (8): 569. doi:10.1038/nrd4090. PMID 23903212. S2CID 20246434.
Zhavoronkov, Alex (2019). "Deep learning enables rapid identification of potent DDR1 kinase inhibitors". Nature Biotechnology. 37 (9): 1038–1040. doi:10.1038/s41587-019-0224-x. PMID 31477924. S2CID 201716327.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (1 January 2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM. pp. 533–540. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210. Archived from the original on 9 May 2021. Retrieved 23 November 2015.
Sathyanarayana, Aarti (1 January 2016). "Sleep Quality Prediction From Wearable Data Using Deep Learning". JMIR mHealth and uHealth. 4 (4): e125. doi:10.2196/mhealth.6562. PMC 5116102. PMID 27815231. S2CID 3821594.
Shalev, Y.; Painsky, A.; Ben-Gal, I. (2022). "Neural Joint Entropy Estimation" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (4): 5488–5500. arXiv:2012.11197. doi:10.1109/TNNLS.2022.3204919. PMID 36155469. S2CID 229339809.
Litjens, Geert; Kooi, Thijs; Bejnordi, Babak Ehteshami; Setio, Arnaud Arindra Adiyoso; Ciompi, Francesco; Ghafoorian, Mohsen; van der Laak, Jeroen A.W.M.; van Ginneken, Bram; Sánchez, Clara I. (December 2017). "A survey on deep learning in medical image analysis". Medical Image Analysis. 42: 60–88. arXiv:1702.05747. Bibcode:2017arXiv170205747L. doi:10.1016/j.media.2017.07.005. PMID 28778026. S2CID 2088679.
Forslid, Gustav; Wieslander, Hakan; Bengtsson, Ewert; Wahlby, Carolina; Hirsch, Jan-Michael; Stark, Christina Runow; Sadanandan, Sajith Kecheril (2017). "Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy". 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). pp. 82–89. doi:10.1109/ICCVW.2017.18. ISBN 9781538610343. S2CID 4728736. Archived from the original on 2021-05-09. Retrieved 2019-11-12.
Dong, Xin; Zhou, Yizhao; Wang, Lantian; Peng, Jingfeng; Lou, Yanbo; Fan, Yiqun (2020). "Liver Cancer Detection Using Hybridized Fully Convolutional Neural Network Based on Deep Learning Framework". IEEE Access. 8: 129889–129898. Bibcode:2020IEEEA...8l9889D. doi:10.1109/ACCESS.2020.3006362. ISSN 2169-3536. S2CID 220733699.
De, Shaunak; Maity, Abhishek; Goel, Vritti; Shitole, Sanjay; Bhattacharya, Avik (2017). "Predicting the popularity of instagram posts for a lifestyle magazine using deep learning". 2017 2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA). pp. 174–177. doi:10.1109/CSCITA.2017.8066548. ISBN 978-1-5090-4381-1. S2CID 35350962.
Kleanthous, Christos; Chatzis, Sotirios (2020). "Gated Mixture Variational Autoencoders for Value Added Tax audit case selection". Knowledge-Based Systems. 188: 105048. doi:10.1016/j.knosys.2019.105048. S2CID 204092079.
Peplow, Mark (2023-11-29). "Google AI and robots join forces to build new materials". Nature. doi:10.1038/d41586-023-03745-5. PMID 38030771. S2CID 265503872.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Oktem, Figen S.; Kar, Oğuzhan Fatih; Bezek, Can Deniz; Kamalabadi, Farzad (2021). "High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction". IEEE Transactions on Computational Imaging. 7: 489–504. arXiv:2008.11625. doi:10.1109/TCI.2021.3075349. ISSN 2333-9403. S2CID 235340737.
Bernhardt, Melanie; Vishnevskiy, Valery; Rau, Richard; Goksel, Orcun (December 2020). "Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67 (12): 2584–2594. arXiv:2006.14395. doi:10.1109/TUFFC.2020.3010186. ISSN 1525-8955. PMID 32746211. S2CID 220055785.
Utgoff, P. E.; Stracuzzi, D. J. (2002). "Many-layered learning". Neural Computation. 14 (10): 2497–2529. doi:10.1162/08997660260293319. PMID 12396572. S2CID 1119517.
Quartz, SR; Sejnowski, TJ (1997). "The neural basis of cognitive development: A constructivist manifesto". Behavioral and Brain Sciences. 20 (4): 537–556. CiteSeerX 10.1.1.41.7854. doi:10.1017/s0140525x97001581. PMID 10097006. S2CID 5818342.
O'Reilly, Randall C. (1 July 1996). "Biologically Plausible Error-Driven Learning Using Local Activation Differences: The Generalized Recirculation Algorithm". Neural Computation. 8 (5): 895–938. doi:10.1162/neco.1996.8.5.895. ISSN 0899-7667. S2CID 2376781.
Testolin, Alberto; Zorzi, Marco (2016). "Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions". Frontiers in Computational Neuroscience. 10: 73. doi:10.3389/fncom.2016.00073. ISSN 1662-5188. PMC 4943066. PMID 27468262. S2CID 9868901.
Testolin, Alberto; Stoianov, Ivilin; Zorzi, Marco (September 2017). "Letter perception emerges from unsupervised deep learning and recycling of natural image features". Nature Human Behaviour. 1 (9): 657–664. doi:10.1038/s41562-017-0186-2. ISSN 2397-3374. PMID 31024135. S2CID 24504018.
Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS Computational Biology. 7 (11): e1002211. Bibcode:2011PLSCB...7E2211B. doi:10.1371/journal.pcbi.1002211. ISSN 1553-7358. PMC 3207943. PMID 22096452. S2CID 7504633.
Cash, S.; Yuste, R. (February 1999). "Linear summation of excitatory inputs by CA1 pyramidal neurons". Neuron. 22 (2): 383–394. doi:10.1016/s0896-6273(00)81098-3. ISSN 0896-6273. PMID 10069343. S2CID 14663106.
Olshausen, B; Field, D (1 August 2004). "Sparse coding of sensory inputs". Current Opinion in Neurobiology. 14 (4): 481–487. doi:10.1016/j.conb.2004.07.007. ISSN 0959-4388. PMID 15321069. S2CID 16560320.
Yamins, Daniel L K; DiCarlo, James J (March 2016). "Using goal-driven deep learning models to understand sensory cortex". Nature Neuroscience. 19 (3): 356–365. doi:10.1038/nn.4244. ISSN 1546-1726. PMID 26906502. S2CID 16970545.
Zorzi, Marco; Testolin, Alberto (19 February 2018). "An emergentist perspective on the origin of number sense". Phil. Trans. R. Soc. B. 373 (1740): 20170043. doi:10.1098/rstb.2017.0043. ISSN 0962-8436. PMC 5784047. PMID 29292348. S2CID 39281431.
Gibney, Elizabeth (2016). "Google AI algorithm masters ancient game of Go". Nature. 529 (7587): 445–446. Bibcode:2016Natur.529..445G. doi:10.1038/529445a. PMID 26819021. S2CID 4460235.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Bradley Knox, W.; Stone, Peter (2008). "TAMER: Training an Agent Manually via Evaluative Reinforcement". 2008 7th IEEE International Conference on Development and Learning. pp. 292–297. doi:10.1109/devlrn.2008.4640845. ISBN 978-1-4244-2661-4. S2CID 5613334.
Mühlhoff, Rainer (6 November 2019). "Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning". New Media & Society. 22 (10): 1868–1884. doi:10.1177/1461444819885334. ISSN 1461-4448. S2CID 209363848.

semanticscholar.org

Schulz, Hannes; Behnke, Sven (1 November 2012). "Deep Learning". KI - Künstliche Intelligenz. 26 (4): 357–363. doi:10.1007/s13218-012-0198-z. ISSN 1610-1987. S2CID 220523562.

serokell.io

A Guide to Deep Learning and Neural Networks, archived from the original on 2020-11-02, retrieved 2020-11-16

singularityhub.com

"AI Is Easy to Fool—Why That Needs to Change". Singularity Hub. 10 October 2017. Archived from the original on 11 October 2017. Retrieved 11 October 2017.

springer.com

link.springer.com

Aizenberg, I.N.; Aizenberg, N.N.; Vandewalle, J. (2000). Multi-Valued and Universal Binary Neurons. Science & Business Media. doi:10.1007/978-1-4757-3115-6. ISBN 978-0-7923-7824-2. Retrieved 27 December 2023.

stanford.edu

nlp.stanford.edu

Socher, Richard; Manning, Christopher. "Deep Learning for NLP" (PDF). Archived (PDF) from the original on 6 July 2014. Retrieved 26 October 2014.
Socher, R.; Perelygin, A.; Wu, J.; Chuang, J.; Manning, C.D.; Ng, A.; Potts, C. (October 2013). "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank" (PDF). Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics: 1631–1642. doi:10.18653/v1/D13-1170. Archived (PDF) from the original on 28 December 2016. Retrieved 21 December 2023.

stanford.edu

Smolensky, Paul (1986). "Chapter 6: Information Processing in Dynamical Systems: Foundations of Harmony Theory" (PDF). In Rumelhart, David E.; McLelland, James L. (eds.). Parallel Distributed Processing: Explorations in the Microstructure of Cognition, Volume 1: Foundations. MIT Press. pp. 194–281. ISBN 0-262-68053-X.

superlectures.com

Li, Deng (September 2014). "Keynote talk: 'Achievements and Challenges of Deep Learning - From Speech Analysis and Recognition To Language and Multimodal Processing'". Interspeech. Archived from the original on 2017-09-26. Retrieved 2017-06-12.

syncedreview.com

"GAN 2.0: NVIDIA's Hyperrealistic Face Generator". SyncedReview.com. December 14, 2018. Retrieved October 3, 2019.

tau.ac.il

iradbengal.sites.tau.ac.il

Shalev, Y.; Painsky, A.; Ben-Gal, I. (2022). "Neural Joint Entropy Estimation" (PDF). IEEE Transactions on Neural Networks and Learning Systems. PP (4): 5488–5500. arXiv:2012.11197. doi:10.1109/TNNLS.2022.3204919. PMID 36155469. S2CID 229339809.

techcrunch.com

"Google's AlphaGo AI wins three-match series against the world's best Go player". TechCrunch. 25 May 2017. Archived from the original on 17 June 2018. Retrieved 17 June 2018.

technologyreview.com

Hof, Robert D. "Is Artificial Intelligence Finally Coming into Its Own?". MIT Technology Review. Archived from the original on 31 March 2019. Retrieved 10 July 2018.
Nvidia Demos a Car Computer Trained with "Deep Learning" (6 January 2015), David Talbot, MIT Technology Review
"DeepMind's protein-folding AI has solved a 50-year-old grand challenge of biology". MIT Technology Review. Retrieved 2024-05-10.
"A Google DeepMind Algorithm Uses Deep Learning and More to Master the Game of Go | MIT Technology Review". MIT Technology Review. Archived from the original on 1 February 2016. Retrieved 30 January 2016.
Knight, Will (14 March 2017). "DARPA is funding projects that will try to open up AI's black boxes". MIT Technology Review. Archived from the original on 4 November 2019. Retrieved 2 November 2017.

techtalks.tv

Eisner, Jason. "Deep Learning of Recursive Structure: Grammar Induction". Archived from the original on 2017-12-30. Retrieved 2015-05-10.

theglobeandmail.com

"Toronto startup has a faster way to discover effective medicines". The Globe and Mail. Archived from the original on 20 October 2015. Retrieved 9 November 2015.

theguardian.com

Alex Hern (18 June 2015). "Yes, androids do dream of electric sheep". The Guardian. Archived from the original on 19 June 2015. Retrieved 20 June 2015.

tntu.edu.ua

elartu.tntu.edu.ua

Gers, Felix A.; Schmidhuber, Jürgen (2001). "LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages". IEEE Transactions on Neural Networks. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962. S2CID 10192330. Archived from the original on 2020-01-26. Retrieved 2020-02-25.
LeCun, Y.; et al. (1998). "Gradient-based learning applied to document recognition". Proceedings of the IEEE. 86 (11): 2278–2324. doi:10.1109/5.726791. S2CID 14542261.

toronto.edu

cs.toronto.edu

Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey (2012). "ImageNet Classification with Deep Convolutional Neural Networks" (PDF). NIPS 2012: Neural Information Processing Systems, Lake Tahoe, Nevada. Archived (PDF) from the original on 2017-01-10. Retrieved 2017-05-24.
Hinton, G. E.; Osindero, S.; Teh, Y. W. (2006). "A Fast Learning Algorithm for Deep Belief Nets" (PDF). Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950. Archived (PDF) from the original on 2015-12-23. Retrieved 2011-07-20.
Dahl, G.; et al. (2013). "Improving DNNs for LVCSR using rectified linear units and dropout" (PDF). ICASSP. Archived (PDF) from the original on 2017-08-12. Retrieved 2017-06-13.

tu-berlin.de

depositonce.tu-berlin.de

Mühlhoff, Rainer (6 November 2019). "Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning". New Media & Society. 22 (10): 1868–1884. doi:10.1177/1461444819885334. ISSN 1461-4448. S2CID 209363848.

tum.de

mediatum.ub.tum.de

Santiago Fernandez, Alex Graves, and Jürgen Schmidhuber (2007). An application of recurrent neural networks to discriminative keyword spotting Archived 2018-11-18 at the Wayback Machine. Proceedings of ICANN (2), pp. 220–229.

u-szeged.hu

publicatio.bibl.u-szeged.hu

Tóth, Laszló (2015). "Phone Recognition with Hierarchical Convolutional Deep Maxout Networks" (PDF). EURASIP Journal on Audio, Speech, and Music Processing. 2015. doi:10.1186/s13636-015-0068-3. S2CID 217950236. Archived (PDF) from the original on 2020-09-24. Retrieved 2019-04-01.

ufrgs.br

inf.ufrgs.br

Alexander Waibel et al., Phoneme Recognition Using Time-Delay Neural Networks IEEE Transactions on Acoustics, Speech, and Signal Processing, Volume 37, No. 3, pp. 328. – 339 March 1989.

upenn.edu

catalog.ldc.upenn.edu

Garofolo, J.S.; Lamel, L.F.; Fisher, W.M.; Fiscus, J.G.; Pallett, D.S.; Dahlgren, N.L.; Zue, V. (1993). TIMIT Acoustic-Phonetic Continuous Speech Corpus. Linguistic Data Consortium. doi:10.35111/17gk-bn40. ISBN 1-58563-019-5. Retrieved 27 December 2023.

utl.pt

users.isr.ist.utl.pt

Bishop, Christopher M. (2006). Pattern Recognition and Machine Learning (PDF). Springer. ISBN 978-0-387-31073-2. Archived (PDF) from the original on 2017-01-11. Retrieved 2017-08-06.

utoronto.ca

csri.utoronto.ca

G. E. Hinton., "Learning multiple layers of representation". Archived 2018-05-22 at the Wayback Machine. Trends in Cognitive Sciences, 11, pp. 428–434, 2007.

uweschmidt.org

research.uweschmidt.org

Schmidt, Uwe; Roth, Stefan. Shrinkage Fields for Effective Image Restoration (PDF). Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. Archived (PDF) from the original on 2018-01-02. Retrieved 2018-01-01.

venturebeat.com

"Cerebras launches new AI supercomputing processor with 2.6 trillion transistors". VentureBeat. 2021-04-20. Retrieved 2022-08-03.
Nuñez, Michael (2023-11-29). "Google DeepMind's materials AI has already discovered 2.2 million new crystals". VentureBeat. Retrieved 2023-12-19.

vutbr.cz

fit.vutbr.cz

Mikolov, T.; et al. (2010). "Recurrent neural network based language model" (PDF). Interspeech: 1045–1048. doi:10.21437/Interspeech.2010-343. S2CID 17048224. Archived (PDF) from the original on 2017-05-16. Retrieved 2017-06-13.

web.archive.org

Krizhevsky, Alex; Sutskever, Ilya; Hinton, Geoffrey (2012). "ImageNet Classification with Deep Convolutional Neural Networks" (PDF). NIPS 2012: Neural Information Processing Systems, Lake Tahoe, Nevada. Archived (PDF) from the original on 2017-01-10. Retrieved 2017-05-24.
"Google's AlphaGo AI wins three-match series against the world's best Go player". TechCrunch. 25 May 2017. Archived from the original on 17 June 2018. Retrieved 17 June 2018.
Bengio, Yoshua (2009). "Learning Deep Architectures for AI" (PDF). Foundations and Trends in Machine Learning. 2 (1): 1–127. CiteSeerX 10.1.1.701.9550. doi:10.1561/2200000006. S2CID 207178999. Archived from the original (PDF) on 4 March 2016. Retrieved 3 September 2015.
Bengio, Yoshua; Lamblin, Pascal; Popovici, Dan; Larochelle, Hugo (2007). Greedy layer-wise training of deep networks (PDF). Advances in neural information processing systems. pp. 153–160. Archived (PDF) from the original on 2019-10-20. Retrieved 2019-10-06.
Rina Dechter (1986). Learning while searching in constraint-satisfaction problems. University of California, Computer Science Department, Cognitive Systems Laboratory.Online Archived 2016-04-19 at the Wayback Machine
Cybenko (1989). "Approximations by superpositions of sigmoidal functions" (PDF). Mathematics of Control, Signals, and Systems. 2 (4): 303–314. Bibcode:1989MCSS....2..303C. doi:10.1007/bf02551274. S2CID 3958369. Archived from the original (PDF) on 10 October 2015.
Lu, Z., Pu, H., Wang, F., Hu, Z., & Wang, L. (2017). The Expressive Power of Neural Networks: A View from the Width Archived 2019-02-13 at the Wayback Machine. Neural Information Processing Systems, 6231-6239.
Deng, L.; Yu, D. (2014). "Deep Learning: Methods and Applications" (PDF). Foundations and Trends in Signal Processing. 7 (3–4): 1–199. doi:10.1561/2000000039. Archived (PDF) from the original on 2016-03-14. Retrieved 2014-10-18.
Bishop, Christopher M. (2006). Pattern Recognition and Machine Learning (PDF). Springer. ISBN 978-0-387-31073-2. Archived (PDF) from the original on 2017-01-11. Retrieved 2017-08-06.
Ivakhnenko, Alexey (1971). "Polynomial theory of complex systems" (PDF). IEEE Transactions on Systems, Man, and Cybernetics. SMC-1 (4): 364–378. doi:10.1109/TSMC.1971.4308320. Archived (PDF) from the original on 2017-08-29. Retrieved 2019-11-05.
Schmidhuber, Juergen (25 Oct 2014). "Who Invented Backpropagation?". IDSIA, Switzerland. Archived from the original on 30 July 2024. Retrieved 14 Sep 2024.
Werbos, Paul (1982). "Applications of advances in nonlinear sensitivity analysis" (PDF). System modeling and optimization. Springer. pp. 762–770. Archived (PDF) from the original on 14 April 2016. Retrieved 2 July 2017.
Rumelhart, David E., Geoffrey E. Hinton, and R. J. Williams. "Learning Internal Representations by Error Propagation Archived 2022-10-13 at the Wayback Machine". David E. Rumelhart, James L. McClelland, and the PDP research group. (editors), Parallel distributed processing: Explorations in the microstructure of cognition, Volume 1: Foundation. MIT Press, 1986.
S. Hochreiter., "Untersuchungen zu dynamischen neuronalen Netzen". Archived 2015-03-06 at the Wayback Machine. Diploma thesis. Institut f. Informatik, Technische Univ. Munich. Advisor: J. Schmidhuber, 1991.
Robinson, T. (1992). "A real-time recurrent error propagation network word recognition system". ICASSP. Icassp'92: 617–620. ISBN 9780780305328. Archived from the original on 2021-05-09. Retrieved 2017-06-12.
Waibel, A.; Hanazawa, T.; Hinton, G.; Shikano, K.; Lang, K. J. (March 1989). "Phoneme recognition using time-delay neural networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 37 (3): 328–339. doi:10.1109/29.21701. hdl:10338.dmlcz/135496. ISSN 0096-3518. S2CID 9563026. Archived (PDF) from the original on 2021-04-27. Retrieved 2019-09-24.
Bengio, Y. (1991). "Artificial Neural Networks and their Application to Speech/Sequence Recognition". McGill University Ph.D. thesis. Archived from the original on 2021-05-09. Retrieved 2017-06-12.
"Acoustic Modeling with Deep Neural Networks Using Raw Time Signal for LVCSR (PDF Download Available)". ResearchGate. Archived from the original on 9 May 2021. Retrieved 14 June 2017.
Graves, Alex; Eck, Douglas; Beringer, Nicole; Schmidhuber, Jürgen (2003). "Biologically Plausible Speech Recognition with LSTM Neural Nets" (PDF). 1st Intl. Workshop on Biologically Inspired Approaches to Advanced Information Technology, Bio-ADIT 2004, Lausanne, Switzerland. pp. 175–184. Archived (PDF) from the original on 2021-05-09. Retrieved 2016-04-09.
Santiago Fernandez, Alex Graves, and Jürgen Schmidhuber (2007). An application of recurrent neural networks to discriminative keyword spotting Archived 2018-11-18 at the Wayback Machine. Proceedings of ICANN (2), pp. 220–229.
Hinton, Geoffrey E. (1 October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. ISSN 1364-6613. PMID 17921042. S2CID 15066318. Archived from the original on 11 October 2013. Retrieved 12 June 2017.
Hinton, G. E.; Osindero, S.; Teh, Y. W. (2006). "A Fast Learning Algorithm for Deep Belief Nets" (PDF). Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. PMID 16764513. S2CID 2309950. Archived (PDF) from the original on 2015-12-23. Retrieved 2011-07-20.
G. E. Hinton., "Learning multiple layers of representation". Archived 2018-05-22 at the Wayback Machine. Trends in Cognitive Sciences, 11, pp. 428–434, 2007.
Yann LeCun (2016). Slides on Deep Learning Online Archived 2016-04-23 at the Wayback Machine
Deng, L.; Hinton, G.; Kingsbury, B. (May 2013). "New types of deep neural network learning for speech recognition and related applications: An overview (ICASSP)" (PDF). Microsoft. Archived (PDF) from the original on 2017-09-26. Retrieved 27 December 2023.
"Deng receives prestigious IEEE Technical Achievement Award - Microsoft Research". Microsoft Research. 3 December 2015. Archived from the original on 16 March 2018. Retrieved 16 March 2018.
Li, Deng (September 2014). "Keynote talk: 'Achievements and Challenges of Deep Learning - From Speech Analysis and Recognition To Language and Multimodal Processing'". Interspeech. Archived from the original on 2017-09-26. Retrieved 2017-06-12.
Yu, D.; Deng, L. (2010). "Roles of Pre-Training and Fine-Tuning in Context-Dependent DBN-HMMs for Real-World Speech Recognition". NIPS Workshop on Deep Learning and Unsupervised Feature Learning. Archived from the original on 2017-10-12. Retrieved 2017-06-14.
Seide, F.; Li, G.; Yu, D. (2011). "Conversational speech transcription using context-dependent deep neural networks". Interspeech 2011. pp. 437–440. doi:10.21437/Interspeech.2011-169. S2CID 398770. Archived from the original on 2017-10-12. Retrieved 2017-06-14.
Deng, Li; Li, Jinyu; Huang, Jui-Ting; Yao, Kaisheng; Yu, Dong; Seide, Frank; Seltzer, Mike; Zweig, Geoff; He, Xiaodong (1 May 2013). "Recent Advances in Deep Learning for Speech Research at Microsoft". Microsoft Research. Archived from the original on 12 October 2017. Retrieved 14 June 2017.
Chellapilla, Kumar; Puri, Sidd; Simard, Patrice (2006), High performance convolutional neural networks for document processing, archived from the original on 2020-05-18, retrieved 2021-02-14
Ciresan, D. C.; Meier, U.; Masci, J.; Gambardella, L.M.; Schmidhuber, J. (2011). "Flexible, High Performance Convolutional Neural Networks for Image Classification" (PDF). International Joint Conference on Artificial Intelligence. doi:10.5591/978-1-57735-516-8/ijcai11-210. Archived (PDF) from the original on 2014-09-29. Retrieved 2017-06-13.
Ciresan, Dan; Giusti, Alessandro; Gambardella, Luca M.; Schmidhuber, Jürgen (2012). Pereira, F.; Burges, C. J. C.; Bottou, L.; Weinberger, K. Q. (eds.). Advances in Neural Information Processing Systems 25 (PDF). Curran Associates, Inc. pp. 2843–2851. Archived (PDF) from the original on 2017-08-09. Retrieved 2017-06-13.
Goodfellow, Ian; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). Generative Adversarial Networks (PDF). Proceedings of the International Conference on Neural Information Processing Systems (NIPS 2014). pp. 2672–2680. Archived (PDF) from the original on 22 November 2019. Retrieved 20 August 2019.
"Prepare, Don't Panic: Synthetic Media and Deepfakes". witness.org. Archived from the original on 2 December 2020. Retrieved 25 November 2020.
Sak, Haşim; Senior, Andrew; Rao, Kanishka; Beaufays, Françoise; Schalkwyk, Johan (September 2015). "Google voice search: faster and more accurate". Archived from the original on 2016-03-09. Retrieved 2016-04-09.
Sak, Hasim; Senior, Andrew; Beaufays, Francoise (2014). "Long Short-Term Memory recurrent neural network architectures for large scale acoustic modeling" (PDF). Archived from the original (PDF) on 24 April 2018.
Zen, Heiga; Sak, Hasim (2015). "Unidirectional Long Short-Term Memory Recurrent Neural Network with Recurrent Output Layer for Low-Latency Speech Synthesis" (PDF). Google.com. ICASSP. pp. 4470–4474. Archived (PDF) from the original on 2021-05-09. Retrieved 2017-06-13.
A Guide to Deep Learning and Neural Networks, archived from the original on 2020-11-02, retrieved 2020-11-16
Szegedy, Christian; Toshev, Alexander; Erhan, Dumitru (2013). "Deep neural networks for object detection". Advances in Neural Information Processing Systems: 2553–2561. Archived from the original on 2017-06-29. Retrieved 2017-06-13.
Rolnick, David; Tegmark, Max (2018). "The power of deeper networks for expressing natural functions". International Conference on Learning Representations. ICLR 2018. Archived from the original on 2021-01-07. Retrieved 2021-01-05.
Hof, Robert D. "Is Artificial Intelligence Finally Coming into Its Own?". MIT Technology Review. Archived from the original on 31 March 2019. Retrieved 10 July 2018.
Gers, Felix A.; Schmidhuber, Jürgen (2001). "LSTM Recurrent Networks Learn Simple Context Free and Context Sensitive Languages". IEEE Transactions on Neural Networks. 12 (6): 1333–1340. doi:10.1109/72.963769. PMID 18249962. S2CID 10192330. Archived from the original on 2020-01-26. Retrieved 2020-02-25.
Sutskever, L.; Vinyals, O.; Le, Q. (2014). "Sequence to Sequence Learning with Neural Networks" (PDF). Proc. NIPS. arXiv:1409.3215. Bibcode:2014arXiv1409.3215S. Archived (PDF) from the original on 2021-05-09. Retrieved 2017-06-13.
Mikolov, T.; et al. (2010). "Recurrent neural network based language model" (PDF). Interspeech: 1045–1048. doi:10.21437/Interspeech.2010-343. S2CID 17048224. Archived (PDF) from the original on 2017-05-16. Retrieved 2017-06-13.
"Learning Precise Timing with LSTM Recurrent Networks (PDF Download Available)". ResearchGate. Archived from the original on 9 May 2021. Retrieved 13 June 2017.
Dahl, G.; et al. (2013). "Improving DNNs for LVCSR using rectified linear units and dropout" (PDF). ICASSP. Archived (PDF) from the original on 2017-08-12. Retrieved 2017-06-13.
"Data Augmentation - deeplearning.ai | Coursera". Coursera. Archived from the original on 1 December 2017. Retrieved 30 November 2017.
Hinton, G. E. (2010). "A Practical Guide to Training Restricted Boltzmann Machines". Tech. Rep. UTML TR 2010-003. Archived from the original on 2021-05-09. Retrieved 2017-06-13.
You, Yang; Buluç, Aydın; Demmel, James (November 2017). "Scaling deep learning on GPU and knights landing clusters". Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis on - SC '17. SC '17, ACM. pp. 1–12. doi:10.1145/3126908.3126912. ISBN 9781450351140. S2CID 8869270. Archived from the original on 29 July 2020. Retrieved 5 March 2018.
Ting Qin, et al. "Continuous CMAC-QRLS and its systolic array". Archived 2018-11-18 at the Wayback Machine. Neural Processing Letters 22.1 (2005): 1-16.
Research, AI (23 October 2015). "Deep Neural Networks for Acoustic Modeling in Speech Recognition". airesearch.com. Archived from the original on 1 February 2016. Retrieved 23 October 2015.
"GPUs Continue to Dominate the AI Accelerator Market for Now". InformationWeek. December 2019. Archived from the original on 10 June 2020. Retrieved 11 June 2020.
Ray, Tiernan (2019). "AI is changing the entire nature of computation". ZDNet. Archived from the original on 25 May 2020. Retrieved 11 June 2020.
"AI and Compute". OpenAI. 16 May 2018. Archived from the original on 17 June 2020. Retrieved 11 June 2020.
Abdel-Hamid, O.; et al. (2014). "Convolutional Neural Networks for Speech Recognition". IEEE/ACM Transactions on Audio, Speech, and Language Processing. 22 (10): 1533–1545. doi:10.1109/taslp.2014.2339736. S2CID 206602362. Archived from the original on 2020-09-22. Retrieved 2018-04-20.
Tóth, Laszló (2015). "Phone Recognition with Hierarchical Convolutional Deep Maxout Networks" (PDF). EURASIP Journal on Audio, Speech, and Music Processing. 2015. doi:10.1186/s13636-015-0068-3. S2CID 217950236. Archived (PDF) from the original on 2020-09-24. Retrieved 2019-04-01.
McMillan, Robert (17 December 2014). "How Skype Used AI to Build Its Amazing New Language Translator | WIRED". Wired. Archived from the original on 8 June 2017. Retrieved 14 June 2017.
"MNIST handwritten digit database, Yann LeCun, Corinna Cortes and Chris Burges". yann.lecun.com. Archived from the original on 2014-01-13. Retrieved 2014-01-28.
Socher, Richard; Manning, Christopher. "Deep Learning for NLP" (PDF). Archived (PDF) from the original on 6 July 2014. Retrieved 26 October 2014.
Socher, Richard; Bauer, John; Manning, Christopher; Ng, Andrew (2013). "Parsing With Compositional Vector Grammars" (PDF). Proceedings of the ACL 2013 Conference. Archived (PDF) from the original on 2014-11-27. Retrieved 2014-09-03.
Socher, R.; Perelygin, A.; Wu, J.; Chuang, J.; Manning, C.D.; Ng, A.; Potts, C. (October 2013). "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank" (PDF). Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics: 1631–1642. doi:10.18653/v1/D13-1170. Archived (PDF) from the original on 28 December 2016. Retrieved 21 December 2023.
Shen, Yelong; He, Xiaodong; Gao, Jianfeng; Deng, Li; Mesnil, Gregoire (1 November 2014). "A Latent Semantic Model with Convolutional-Pooling Structure for Information Retrieval". Microsoft Research. Archived from the original on 27 October 2017. Retrieved 14 June 2017.
Huang, Po-Sen; He, Xiaodong; Gao, Jianfeng; Deng, Li; Acero, Alex; Heck, Larry (1 October 2013). "Learning Deep Structured Semantic Models for Web Search using Clickthrough Data". Microsoft Research. Archived from the original on 27 October 2017. Retrieved 14 June 2017.
Gao, Jianfeng; He, Xiaodong; Yih, Scott Wen-tau; Deng, Li (1 June 2014). "Learning Continuous Phrase Representations for Translation Modeling". Microsoft Research. Archived from the original on 27 October 2017. Retrieved 14 June 2017.
"Deep Learning for Natural Language Processing: Theory and Practice (CIKM2014 Tutorial) - Microsoft Research". Microsoft Research. Archived from the original on 13 March 2017. Retrieved 14 June 2017.
Turovsky, Barak (15 November 2016). "Found in translation: More accurate, fluent sentences in Google Translate". The Keyword Google Blog. Archived from the original on 7 April 2017. Retrieved 23 March 2017.
Schuster, Mike; Johnson, Melvin; Thorat, Nikhil (22 November 2016). "Zero-Shot Translation with Google's Multilingual Neural Machine Translation System". Google Research Blog. Archived from the original on 10 July 2017. Retrieved 23 March 2017.
Metz, Cade (27 September 2016). "An Infusion of AI Makes Google Translate More Powerful Than Ever". Wired. Archived from the original on 8 November 2020. Retrieved 12 October 2017.
Boitet, Christian; Blanchon, Hervé; Seligman, Mark; Bellynck, Valérie (2010). "MT on and for the Web" (PDF). Archived from the original (PDF) on 29 March 2017. Retrieved 1 December 2016.
"Merck Molecular Activity Challenge". kaggle.com. Archived from the original on 2020-07-16. Retrieved 2020-07-16.
"Multi-task Neural Networks for QSAR Predictions | Data Science Association". www.datascienceassn.org. Archived from the original on 30 April 2017. Retrieved 14 June 2017.
"NCATS Announces Tox21 Data Challenge Winners". Archived from the original on 2015-09-08. Retrieved 2015-03-05.
"NCATS Announces Tox21 Data Challenge Winners". Archived from the original on 28 February 2015. Retrieved 5 March 2015.
"Toronto startup has a faster way to discover effective medicines". The Globe and Mail. Archived from the original on 20 October 2015. Retrieved 9 November 2015.
"Startup Harnesses Supercomputers to Seek Cures". KQED Future of You. 27 May 2015. Archived from the original on 24 December 2015. Retrieved 9 November 2015.
Gregory, Barber. "A Molecule Designed By AI Exhibits 'Druglike' Qualities". Wired. Archived from the original on 2020-04-30. Retrieved 2019-09-05.
van den Oord, Aaron; Dieleman, Sander; Schrauwen, Benjamin (2013). Burges, C. J. C.; Bottou, L.; Welling, M.; Ghahramani, Z.; Weinberger, K. Q. (eds.). Advances in Neural Information Processing Systems 26 (PDF). Curran Associates, Inc. pp. 2643–2651. Archived (PDF) from the original on 2017-05-16. Retrieved 2017-06-14.
Elkahky, Ali Mamdouh; Song, Yang; He, Xiaodong (1 May 2015). "A Multi-View Deep Learning Approach for Cross Domain User Modeling in Recommendation Systems". Microsoft Research. Archived from the original on 25 January 2018. Retrieved 14 June 2017.
Chicco, Davide; Sadowski, Peter; Baldi, Pierre (1 January 2014). "Deep autoencoder neural networks for gene ontology annotation predictions". Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics. ACM. pp. 533–540. doi:10.1145/2649387.2649442. hdl:11311/964622. ISBN 9781450328944. S2CID 207217210. Archived from the original on 9 May 2021. Retrieved 23 November 2015.
Forslid, Gustav; Wieslander, Hakan; Bengtsson, Ewert; Wahlby, Carolina; Hirsch, Jan-Michael; Stark, Christina Runow; Sadanandan, Sajith Kecheril (2017). "Deep Convolutional Neural Networks for Detecting Cellular Changes Due to Malignancy". 2017 IEEE International Conference on Computer Vision Workshops (ICCVW). pp. 82–89. doi:10.1109/ICCVW.2017.18. ISBN 9781538610343. S2CID 4728736. Archived from the original on 2021-05-09. Retrieved 2019-11-12.
"Colorizing and Restoring Old Images with Deep Learning". FloydHub Blog. 13 November 2018. Archived from the original on 11 October 2019. Retrieved 11 October 2019.
Schmidt, Uwe; Roth, Stefan. Shrinkage Fields for Effective Image Restoration (PDF). Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on. Archived (PDF) from the original on 2018-01-02. Retrieved 2018-01-01.
Czech, Tomasz (28 June 2018). "Deep learning: the next frontier for money laundering detection". Global Banking and Finance Review. Archived from the original on 2018-11-16. Retrieved 2018-07-15.
"Army researchers develop new algorithms to train robots". EurekAlert!. Archived from the original on 28 August 2018. Retrieved 29 August 2018.
Metz, C. (12 December 2013). "Facebook's 'Deep Learning' Guru Reveals the Future of AI". Wired. Archived from the original on 28 March 2014. Retrieved 26 August 2017.
"A Google DeepMind Algorithm Uses Deep Learning and More to Master the Game of Go | MIT Technology Review". MIT Technology Review. Archived from the original on 1 February 2016. Retrieved 30 January 2016.
Metz, Cade (6 November 2017). "A.I. Researchers Leave Elon Musk Lab to Begin Robotics Start-Up". The New York Times. Archived from the original on 7 July 2019. Retrieved 5 July 2019.
"Talk to the Algorithms: AI Becomes a Faster Learner". governmentciomedia.com. 16 May 2018. Archived from the original on 28 August 2018. Retrieved 29 August 2018.
Marcus, Gary (14 January 2018). "In defense of skepticism about deep learning". Gary Marcus. Archived from the original on 12 October 2018. Retrieved 11 October 2018.
Knight, Will (14 March 2017). "DARPA is funding projects that will try to open up AI's black boxes". MIT Technology Review. Archived from the original on 4 November 2019. Retrieved 2 November 2017.
Marcus, Gary (November 25, 2012). "Is "Deep Learning" a Revolution in Artificial Intelligence?". The New Yorker. Archived from the original on 2009-11-27. Retrieved 2017-06-14.
Alexander Mordvintsev; Christopher Olah; Mike Tyka (17 June 2015). "Inceptionism: Going Deeper into Neural Networks". Google Research Blog. Archived from the original on 3 July 2015. Retrieved 20 June 2015.
Alex Hern (18 June 2015). "Yes, androids do dream of electric sheep". The Guardian. Archived from the original on 19 June 2015. Retrieved 20 June 2015.
Goertzel, Ben (2015). "Are there Deep Reasons Underlying the Pathologies of Today's Deep Learning Algorithms?" (PDF). Archived (PDF) from the original on 2015-05-13. Retrieved 2015-05-10.
Eisner, Jason. "Deep Learning of Recursive Structure: Grammar Induction". Archived from the original on 2017-12-30. Retrieved 2015-05-10.
"Hackers Have Already Started to Weaponize Artificial Intelligence". Gizmodo. 11 September 2017. Archived from the original on 11 October 2019. Retrieved 11 October 2019.
"How hackers can force AI to make dumb mistakes". The Daily Dot. 18 June 2018. Archived from the original on 11 October 2019. Retrieved 11 October 2019.
"AI Is Easy to Fool—Why That Needs to Change". Singularity Hub. 10 October 2017. Archived from the original on 11 October 2017. Retrieved 11 October 2017.
Gibney, Elizabeth (2017). "The scientist who spots fake videos". Nature. doi:10.1038/nature.2017.22784. Archived from the original on 2017-10-10. Retrieved 2017-10-11.

werbos.com

Werbos, Paul (1982). "Applications of advances in nonlinear sensitivity analysis" (PDF). System modeling and optimization. Springer. pp. 762–770. Archived (PDF) from the original on 14 April 2016. Retrieved 2 July 2017.

wikidata.org

Sepp Hochreiter; Jürgen Schmidhuber (21 August 1995), Long Short Term Memory, Wikidata Q98967430

wiley.com

onlinelibrary.wiley.com

Elman, Jeffrey L. (March 1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. doi:10.1207/s15516709cog1402_1. ISSN 0364-0213.

wired.com

McMillan, Robert (17 December 2014). "How Skype Used AI to Build Its Amazing New Language Translator | WIRED". Wired. Archived from the original on 8 June 2017. Retrieved 14 June 2017.
Metz, Cade (27 September 2016). "An Infusion of AI Makes Google Translate More Powerful Than Ever". Wired. Archived from the original on 8 November 2020. Retrieved 12 October 2017.
Gregory, Barber. "A Molecule Designed By AI Exhibits 'Druglike' Qualities". Wired. Archived from the original on 2020-04-30. Retrieved 2019-09-05.
Metz, C. (12 December 2013). "Facebook's 'Deep Learning' Guru Reveals the Future of AI". Wired. Archived from the original on 28 March 2014. Retrieved 26 August 2017.

witness.org

lab.witness.org

"Prepare, Don't Panic: Synthetic Media and Deepfakes". witness.org. Archived from the original on 2 December 2020. Retrieved 25 November 2020.

worldcat.org

search.worldcat.org

Schulz, Hannes; Behnke, Sven (1 November 2012). "Deep Learning". KI - Künstliche Intelligenz. 26 (4): 357–363. doi:10.1007/s13218-012-0198-z. ISSN 1610-1987. S2CID 220523562.
Fradkov, Alexander L. (2020-01-01). "Early History of Machine Learning". IFAC-PapersOnLine. 21st IFAC World Congress. 53 (2): 1385–1390. doi:10.1016/j.ifacol.2020.12.1888. ISSN 2405-8963. S2CID 235081987.
Rosenblatt, F. (1958). "The perceptron: A probabilistic model for information storage and organization in the brain". Psychological Review. 65 (6): 386–408. doi:10.1037/h0042519. ISSN 1939-1471. PMID 13602029.
Rumelhart, David E.; Hinton, Geoffrey E.; Williams, Ronald J. (October 1986). "Learning representations by back-propagating errors". Nature. 323 (6088): 533–536. Bibcode:1986Natur.323..533R. doi:10.1038/323533a0. ISSN 1476-4687.
Elman, Jeffrey L. (March 1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. doi:10.1207/s15516709cog1402_1. ISSN 0364-0213.
Ackley, David H.; Hinton, Geoffrey E.; Sejnowski, Terrence J. (1985-01-01). "A learning algorithm for boltzmann machines". Cognitive Science. 9 (1): 147–169. doi:10.1016/S0364-0213(85)80012-4. ISSN 0364-0213.
Qian, Ning; Sejnowski, Terrence J. (1988-08-20). "Predicting the secondary structure of globular proteins using neural network models". Journal of Molecular Biology. 202 (4): 865–884. doi:10.1016/0022-2836(88)90564-5. ISSN 0022-2836. PMID 3172241.
Morgan, Nelson; Bourlard, Hervé; Renals, Steve; Cohen, Michael; Franco, Horacio (1 August 1993). "Hybrid neural network/hidden markov model systems for continuous speech recognition". International Journal of Pattern Recognition and Artificial Intelligence. 07 (4): 899–916. doi:10.1142/s0218001493000455. ISSN 0218-0014.
Waibel, A.; Hanazawa, T.; Hinton, G.; Shikano, K.; Lang, K. J. (March 1989). "Phoneme recognition using time-delay neural networks" (PDF). IEEE Transactions on Acoustics, Speech, and Signal Processing. 37 (3): 328–339. doi:10.1109/29.21701. hdl:10338.dmlcz/135496. ISSN 0096-3518. S2CID 9563026. Archived (PDF) from the original on 2021-04-27. Retrieved 2019-09-24.
Hinton, Geoffrey E. (1 October 2007). "Learning multiple layers of representation". Trends in Cognitive Sciences. 11 (10): 428–434. doi:10.1016/j.tics.2007.09.004. ISSN 1364-6613. PMID 17921042. S2CID 15066318. Archived from the original on 11 October 2013. Retrieved 12 June 2017.
Hinton, Geoffrey E.; Osindero, Simon; Teh, Yee-Whye (July 2006). "A Fast Learning Algorithm for Deep Belief Nets". Neural Computation. 18 (7): 1527–1554. doi:10.1162/neco.2006.18.7.1527. ISSN 0899-7667. PMID 16764513.
Hinton, Geoffrey E. (2009-05-31). "Deep belief networks". Scholarpedia. 4 (5): 5947. Bibcode:2009SchpJ...4.5947H. doi:10.4249/scholarpedia.5947. ISSN 1941-6016.
Cireşan, Dan Claudiu; Meier, Ueli; Gambardella, Luca Maria; Schmidhuber, Jürgen (21 September 2010). "Deep, Big, Simple Neural Nets for Handwritten Digit Recognition". Neural Computation. 22 (12): 3207–3220. arXiv:1003.0358. doi:10.1162/neco_a_00052. ISSN 0899-7667. PMID 20858131. S2CID 1918673.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda (January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 1476-4687. PMID 26819042. S2CID 515925.
Hochreiter, Sepp; Schmidhuber, Jürgen (1 November 1997). "Long Short-Term Memory". Neural Computation. 9 (8): 1735–1780. doi:10.1162/neco.1997.9.8.1735. ISSN 0899-7667. PMID 9377276. S2CID 1915014.
Choi, Edward; Schuetz, Andy; Stewart, Walter F.; Sun, Jimeng (13 August 2016). "Using recurrent neural network models for early detection of heart failure onset". Journal of the American Medical Informatics Association. 24 (2): 361–370. doi:10.1093/jamia/ocw112. ISSN 1067-5027. PMC 5391725. PMID 27521897.
Dong, Xin; Zhou, Yizhao; Wang, Lantian; Peng, Jingfeng; Lou, Yanbo; Fan, Yiqun (2020). "Liver Cancer Detection Using Hybridized Fully Convolutional Neural Network Based on Deep Learning Framework". IEEE Access. 8: 129889–129898. Bibcode:2020IEEEA...8l9889D. doi:10.1109/ACCESS.2020.3006362. ISSN 2169-3536. S2CID 220733699.
Lyakhov, Pavel Alekseevich; Lyakhova, Ulyana Alekseevna; Nagornov, Nikolay Nikolaevich (2022-04-03). "System for the Recognizing of Pigmented Skin Lesions with Fusion and Analysis of Heterogeneous Data Based on a Multimodal Neural Network". Cancers. 14 (7): 1819. doi:10.3390/cancers14071819. ISSN 2072-6694. PMC 8997449. PMID 35406591.
Merchant, Amil; Batzner, Simon; Schoenholz, Samuel S.; Aykol, Muratahan; Cheon, Gowoon; Cubuk, Ekin Dogus (December 2023). "Scaling deep learning for materials discovery". Nature. 624 (7990): 80–85. Bibcode:2023Natur.624...80M. doi:10.1038/s41586-023-06735-9. ISSN 1476-4687. PMC 10700131. PMID 38030720.
Raissi, M.; Perdikaris, P.; Karniadakis, G. E. (2019-02-01). "Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations". Journal of Computational Physics. 378: 686–707. Bibcode:2019JCoPh.378..686R. doi:10.1016/j.jcp.2018.10.045. ISSN 0021-9991. OSTI 1595805. S2CID 57379996.
Mao, Zhiping; Jagtap, Ameya D.; Karniadakis, George Em (2020-03-01). "Physics-informed neural networks for high-speed flows". Computer Methods in Applied Mechanics and Engineering. 360: 112789. Bibcode:2020CMAME.360k2789M. doi:10.1016/j.cma.2019.112789. ISSN 0045-7825. S2CID 212755458.
Oktem, Figen S.; Kar, Oğuzhan Fatih; Bezek, Can Deniz; Kamalabadi, Farzad (2021). "High-Resolution Multi-Spectral Imaging With Diffractive Lenses and Learned Reconstruction". IEEE Transactions on Computational Imaging. 7: 489–504. arXiv:2008.11625. doi:10.1109/TCI.2021.3075349. ISSN 2333-9403. S2CID 235340737.
Bernhardt, Melanie; Vishnevskiy, Valery; Rau, Richard; Goksel, Orcun (December 2020). "Training Variational Networks With Multidomain Simulations: Speed-of-Sound Image Reconstruction". IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 67 (12): 2584–2594. arXiv:2006.14395. doi:10.1109/TUFFC.2020.3010186. ISSN 1525-8955. PMID 32746211. S2CID 220055785.
Lam, Remi; Sanchez-Gonzalez, Alvaro; Willson, Matthew; Wirnsberger, Peter; Fortunato, Meire; Alet, Ferran; Ravuri, Suman; Ewalds, Timo; Eaton-Rosen, Zach; Hu, Weihua; Merose, Alexander; Hoyer, Stephan; Holland, George; Vinyals, Oriol; Stott, Jacklynn (2023-12-22). "Learning skillful medium-range global weather forecasting". Science. 382 (6677): 1416–1421. arXiv:2212.12794. Bibcode:2023Sci...382.1416L. doi:10.1126/science.adi2336. ISSN 0036-8075. PMID 37962497.
Mazzoni, P.; Andersen, R. A.; Jordan, M. I. (15 May 1991). "A more biologically plausible learning rule for neural networks". Proceedings of the National Academy of Sciences. 88 (10): 4433–4437. Bibcode:1991PNAS...88.4433M. doi:10.1073/pnas.88.10.4433. ISSN 0027-8424. PMC 51674. PMID 1903542.
O'Reilly, Randall C. (1 July 1996). "Biologically Plausible Error-Driven Learning Using Local Activation Differences: The Generalized Recirculation Algorithm". Neural Computation. 8 (5): 895–938. doi:10.1162/neco.1996.8.5.895. ISSN 0899-7667. S2CID 2376781.
Testolin, Alberto; Zorzi, Marco (2016). "Probabilistic Models and Generative Neural Networks: Towards an Unified Framework for Modeling Normal and Impaired Neurocognitive Functions". Frontiers in Computational Neuroscience. 10: 73. doi:10.3389/fncom.2016.00073. ISSN 1662-5188. PMC 4943066. PMID 27468262. S2CID 9868901.
Testolin, Alberto; Stoianov, Ivilin; Zorzi, Marco (September 2017). "Letter perception emerges from unsupervised deep learning and recycling of natural image features". Nature Human Behaviour. 1 (9): 657–664. doi:10.1038/s41562-017-0186-2. ISSN 2397-3374. PMID 31024135. S2CID 24504018.
Buesing, Lars; Bill, Johannes; Nessler, Bernhard; Maass, Wolfgang (3 November 2011). "Neural Dynamics as Sampling: A Model for Stochastic Computation in Recurrent Networks of Spiking Neurons". PLOS Computational Biology. 7 (11): e1002211. Bibcode:2011PLSCB...7E2211B. doi:10.1371/journal.pcbi.1002211. ISSN 1553-7358. PMC 3207943. PMID 22096452. S2CID 7504633.
Cash, S.; Yuste, R. (February 1999). "Linear summation of excitatory inputs by CA1 pyramidal neurons". Neuron. 22 (2): 383–394. doi:10.1016/s0896-6273(00)81098-3. ISSN 0896-6273. PMID 10069343. S2CID 14663106.
Olshausen, B; Field, D (1 August 2004). "Sparse coding of sensory inputs". Current Opinion in Neurobiology. 14 (4): 481–487. doi:10.1016/j.conb.2004.07.007. ISSN 0959-4388. PMID 15321069. S2CID 16560320.
Yamins, Daniel L K; DiCarlo, James J (March 2016). "Using goal-driven deep learning models to understand sensory cortex". Nature Neuroscience. 19 (3): 356–365. doi:10.1038/nn.4244. ISSN 1546-1726. PMID 26906502. S2CID 16970545.
Zorzi, Marco; Testolin, Alberto (19 February 2018). "An emergentist perspective on the origin of number sense". Phil. Trans. R. Soc. B. 373 (1740): 20170043. doi:10.1098/rstb.2017.0043. ISSN 0962-8436. PMC 5784047. PMID 29292348. S2CID 39281431.
Silver, David; Huang, Aja; Maddison, Chris J.; Guez, Arthur; Sifre, Laurent; Driessche, George van den; Schrittwieser, Julian; Antonoglou, Ioannis; Panneershelvam, Veda; Lanctot, Marc; Dieleman, Sander; Grewe, Dominik; Nham, John; Kalchbrenner, Nal; Sutskever, Ilya; Lillicrap, Timothy; Leach, Madeleine; Kavukcuoglu, Koray; Graepel, Thore; Hassabis, Demis (28 January 2016). "Mastering the game of Go with deep neural networks and tree search". Nature. 529 (7587): 484–489. Bibcode:2016Natur.529..484S. doi:10.1038/nature16961. ISSN 0028-0836. PMID 26819042. S2CID 515925.
Mühlhoff, Rainer (6 November 2019). "Human-aided artificial intelligence: Or, how to run large computations in human brains? Toward a media sociology of machine learning". New Media & Society. 22 (10): 1868–1884. doi:10.1177/1461444819885334. ISSN 1461-4448. S2CID 209363848.

zdnet.com

Ray, Tiernan (2019). "AI is changing the entire nature of computation". ZDNet. Archived from the original on 25 May 2020. Retrieved 11 June 2020.

zenodo.org

Abdel-Hamid, O.; et al. (2014). "Convolutional Neural Networks for Speech Recognition". IEEE/ACM Transactions on Audio, Speech, and Language Processing. 22 (10): 1533–1545. doi:10.1109/taslp.2014.2339736. S2CID 206602362. Archived from the original on 2020-09-22. Retrieved 2018-04-20.